74 Senior Deep Learning Engineer jobs in Toronto

Job Description

Job Description

Salary:

About TheAILabb:

TheAILabb is a leading innovation company specializing in AI-powered digital solutions, mobile app development, and emerging technologies. We leverage data-driven insights to enhance digital experiences and drive business growth. We are looking for a Machine Learning (ML) Developer to help translate raw data into meaningful insights that drive strategic decision-making.

Role Overview:
As anML Developer at AILabb , you will be responsible for developing and optimizingmachine learning models , integrating AI-driven features into applications, and collaborating with data scientists, engineers, and product teams to build next-gen intelligent solutions. You will work on a variety of projects, fromcomputer vision andNLP topredictive analytics andrecommendation systems .

Key Responsibilities:
Model Development & Optimization: Design, implement, and optimizeML models for various AI applications.
Data Processing & Feature Engineering: Clean, preprocess, and transform structured and unstructured data for ML pipelines.
Model Deployment & MLOps: Deploy models into production using tools likeTensorFlow Serving, MLflow, or Kubeflow .
AI Integration: Embed ML capabilities into mobile apps, web platforms, and enterprise applications.
Performance Monitoring & Continuous Learning: Track model performance, retrain models, and enhance accuracy.
Collaboration: Work closely withdata engineers, software developers, and product managers to align AI solutions with business goals.
Research & Innovation: Stay updated on the latest advancements in AI/ML and apply new techniques to improve solutions.Required Skills & Qualifications:
Programming & ML Frameworks:
Proficiency inPython (NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch).
Experience withdeep learning architectures (CNNs, RNNs, Transformers).
Strong understanding ofsupervised and unsupervised learning techniques .
Data Handling & Processing:
Experience withSQL and NoSQL databases (PostgreSQL, MongoDB).
Knowledge ofbig data technologies (Spark, Hadoop) is a plus.
Cloud & Deployment:
Familiarity withAWS, GCP, or Azure AI/ML services.
Experience deploying models usingDocker, Kubernetes, or serverless architectures .
MLOps & Model Performance Optimization:
Understanding ofmodel lifecycle management, A/B testing, and continuous learning .
Experience withmodel monitoring and drift detection .

Soft Skills:
Strong problem-solving and analytical thinking.
Ability to work in a fast-paced, agile development environment.
Excellent communication skills for collaborating with cross-functional teams.

Nice-to-Have:
Experience withNLP, Generative AI (LLMs), or Computer Vision .
Knowledge ofReinforcement Learning or Time-Series Forecasting .
Familiarity withedge AI for mobile and IoT applications.

Why Join Us?

Work on large-scalecloud-based data platforms with cutting-edge technologies.
Collaborate with a dynamic, innovative, and data-driven team.
Competitive salary
Opportunities for career growth and continuous learning.

Why youll love TheA I Labb?

We are proud to be certified as a Great Place to Work, Canada. We're a motivated team with laser-focused mission to create exceptional experiences. At TheAILabb, our culture is geared towards creativity, collaboration, and flexibility.

Acknowledge and recognize employee efforts by having awards (Employee of the month, Employee with Most Growth, Leadership Award etc.)

We encourage a healthy lifestyle by incorporating fitness challenge incentives in our Company

TheAILabbs strong values and principles guide our employees to work with honesty, integrity, teamwork, and empathy.

At TheAILabb, we believe diversity and inclusion is a strength we cultivate. We are proud to be an equal opportunity employer, and we do not discriminate based on race, gender, ethnicity, citizenship, national origin, religion, sexual orientation, age, marital status, disability, veteran status or any other legally protected status.

Our work environment welcomes equity, inclusiveness, and diversity by providing accommodations throughout the recruitment process and during your employment here. If you require accommodation, please let us know and we will work with you to meet your needs. Please contact us at

So, if you are looking for your next challenge, then this is your chance to join our team of exceptionally talented, creative, and innovative professionals working towards a unified goal.

Job Description

Job Description

Salary:

About Us:

The AppLabb is a leading innovation company specializing in AI-powered digital solutions, mobile app development, and emerging technologies. We leverage data-driven insights to enhance digital experiences and drive business growth. We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making.

The Opportunity

Summary

We are seeking an experienced Senior Machine Learning Engineer to design, develop, and deploy scalable ML solutions in production environments. You will work closely with data scientists, engineers, and product teams to build robust systems that deliver business-critical AI features. This role requires hands-on expertise in building and operationalizing machine learning models using modern ML frameworks and cloud infrastructure.

What you will do?

• Architect, build, and deploy end-to-end ML pipelines for production workloads.

• Design scalable and resilient ML systems using frameworks such as PyTorch and TensorFlow.

• Operationalize ML models using containerized environments (Docker, Kubernetes) and orchestration tools like Cloud Composer (Airflow) on Cloud Environments (AWS, Azure, GCP)

• Integrate ML solutions with data warehouses like Snowflake, DataBricks or BigQueryfor training and inference at scale.

• Collaborate with cross-functional teams to define requirements and deliver impactful AI features.

• Ensure CI/CD best practices for ML deployments, including monitoring, versioning, and rollback strategies.

Optimize model performance and system efficiency to meet production level SLAs.

What you'll need?

• 5+ years of experience designing and deploying production-grade ML systems at scale.

• Strong knowledge of PyTorch, TensorFlow, and modern ML model lifecycle management.

• Hands-on experience with AWS, Azure or GCP.

• Expertise in Kubernetes, Docker, and workflow orchestration tools such as Cloud Composer or Airflow.

• Proficiency with SQL and experience working with Snowflake, DataBricks or BigQuery.

• Solid understanding of MLOps practices: reproducibility, model monitoring, automated retraining.

• Strong programming skills in Python; experience with LangChain, LangGraph, or related frameworks is a plus.

• Excellent communication and leadership skills, with a proven ability to work in collaborative teams.
  
  Competencies
  
  • Experience building RAG (Retrieval-Augmented Generation) or LLM-based systems in production.
  • Knowledge of distributed systems and streaming data pipelines.
  • Certifications in Cloud Architectures
  
  
  

Why Join Us?

Work on large-scalecloud-based data platforms with cutting-edge technologies.
Collaborate with a dynamic, innovative, and data-driven team.
Competitive salary
Opportunities for career growth and continuous learning.

Why youll love TheAppLabb?
We are proud to be certified as a Great Place to Work, Canada. We're a motivated team with laser-focused mission to create exceptional experiences. At TheAppLabb, our culture is geared towards creativity, collaboration, and flexibility.

Acknowledge and recognize employee efforts by having awards (Employee of the month, Employee with Most Growth, Leadership Award etc.)
We encourage a healthy lifestyle by incorporating fitness challenge incentives in our Company

TheAppLabbs strong values and principles guide our employees to work with honesty, integrity, teamwork, and empathy.

At TheAppLabb, we believe diversity and inclusion is a strength we cultivate. We are proud to be an equal opportunity employer, and we do not discriminate based on race, gender, ethnicity, citizenship, national origin, religion, sexual orientation, age, marital status, disability, veteran status or any other legally protected status.

Our work environment welcomes equity, inclusiveness, and diversity by providing accommodations throughout the recruitment process and during your employment here. If you require accommodation, please let us know and we will work with you to meet your needs. Please contact us at

So, if you are looking for your next challenge, then this is your chance to join our team of exceptionally talented, creative, and innovative professionals working towards a unified goal.

Job Description

Job Description

Company Description

You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities. 

Job Description

We are looking for Data Scientists who are passionate about solving real world problems. You enjoy working with both structured and/or unstructured data and are motivated to productize scalable machine learning models. Critical thinking and problem-solving skills are essential for this role.

Qualifications

• BS (or higher, e.g., MS, or PhD) in Computer Science or related engineering field involving coding
• Experienced implementing and scaling machine learning models in production environments 
• Strong understanding of machine learning theory
• Hands on experience with Statistics
• Capable of quickly implementing prototypes of cutting-edge research papers
• Proficient in Python (i.e. Pandas, Numpy, scikit-learn, etc), R, TensorFlow, amongst other data science related tools and libraries
• Analytical mind and strong business acumen

If you're passionate about data science and is hungry to learn, please apply!

Additional Information

• We have competitive compensation.
• Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management.

Job Description

Job Description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a motivated and passionate Machine Learning Engineers for our team.

As part of this job, you will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Creating Scalable Machine Learning systems that are highly performant
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

Requirements

• Bachelor's degree or higher in computer science or related, with 5+ years of work experience
• Ability to collaborate with Data Engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments
• Ability to manage the infrastructure and data pipelines needed to bring ML solution to production
• End-to-end understanding of applications being created and maintain scalable machine learning solutions in production
• Ability to abstract complexity of production for machine learning using containers
• Ability to troubleshoot production machine learning model issues, including recommendations for retrain, revalidate, and improvements
• Experience with Big Data Projects using multiple types of structured and unstructured data
• Ability to work with a global team, playing a key role in communicating problem context to the remote teams
• Excellent communication and teamwork skills

Additional Skills Required:

• Python, Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
• Test-driven development (prefer py. test/nose), experience with Cloud environments
• Proficiency in statistical tools, relational databases, and expertise in programming language like python/SQL is desired.

Good to have:

• Knowledge of ML frameworks like Scikitlearn, Tensorflow, Keras, etc.
• Knowledge of MLflow, Airflow, Kubernetes
• Knowledge on any of the cloud-native MLaaS offerings like AWS SageMaker, AzureML, or Google AI platform

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

**Job Requisition ID #**
25WD85983
_French job description to follow!/La description de poste en français se trouve plus bas!_
**Position Overview**
Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. We're enhancing our applications with cloud-native capabilities, including data at scale, edge computing, AI-based solutions, and advanced 3D modeling and graphics. This innovation is happening across our flagship products-AutoCAD, Revit, and Construction Cloud-and Forma, our new Industry Cloud.
As a Machine Learning Developer/Engineer on the AEC Solutions team, you will join a team of technologists to help build foundation models and generative AI tools for the AEC industry. You will work collaboratively to create and interpret design data that can enhance design and engineering workflows.
**Report:** You will report to the Machine Learning Manager in the Architecture, Engineering, and Construction (AEC) Solutions Team.
**Location:** We support hybrid work, and you work near our Boston, Massachusetts or Toronto, Canada offices.
**Responsibilities**
+ Architect and guide the implementation of scalable data pipelines and architectures
+ Work with large-scale multimodal datasets (text, 2D/3D geometry, and structured data), developing advanced preprocessing, augmentation, and content understanding techniques
+ Architect, develop, and optimize production-level ML solutions, focusing on scalability and reliability, while contributing to engineering best practices
+ Establish best practices for model experimentation, evaluation, and optimization
+ Contribute to technical execution by writing well-structured, high-performance code for production ML pipelines
+ Perform in-depth requirements analysis, collaborating with team members at different levels and documenting solutions
+ Set the technical direction by identifying key challenges and defining innovative solutions
+ Communicate technical findings effectively, influencing stakeholders through quantitative analysis, qualitative insights, and clear visual presentations
+ Mentor and guide junior engineers, fostering a culture of technical excellence and knowledge-sharing within the team
**Minimum Qualifications**
+ An MS in Machine Learning, Artificial Intelligence, Mathematics, Statistics, Computer Science, or a related field
+ 10+ years of experience in machine learning engineering or a related field, with a proven track record of leadership and hands-on implementation
+ Expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Lightning, Ray)
+ Experience with LLMs and related technologies, including frameworks, embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems, in production settings
+ Deep understanding of data modeling, system architectures, and processing techniques, including 2D/3D geometric data representations
+ Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development
+ Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency
+ Proven ability to translate theoretical concepts into practical solutions and prototype implementations
+ Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation
+ Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams
**Preferred Qualifications**
+ Background in Architecture, Engineering, or Construction
+ Extensive experience in data preparation, hyper-parameter selection; acceleration techniques; and optimization methods
+ Proficiency in parallel and distributed computing techniques, with hands-on experience using platforms like Spark, Ray, or similar distributed systems for large-scale data processing and model training
+ Proven record in developing and deploying high-scale machine learning algorithms in production environments
**Ideal Candidate**
+ You are passionate about solving problems for AEC (Architecture, Engineering, and Construction) customers by applying machine learning techniques
+ You are comfortable driving progress in newly forming, ambiguous areas where learning and adaptability are key
+ You lead by doing, combining technical leadership with hands-on implementation
+ You easily collaborate with others and are comfortable with minimal direction
+ You constantly strive to learn new technologies and methodologies
+ You seek innovative solutions to difficult technical problems and iterate quickly on ideas
+ You are unafraid to experiment, share your ideas openly, and fail fast
---
**Description du poste**
Autodesk est à la tête de la transformation de l'industrie AEC, en intégrant la technologie de l'IA dans nos produits. Nous améliorons nos applications avec des capacités cloud-natives, y compris les données à l'échelle, l'edge computing, les solutions basées sur l'IA, ainsi que la modélisation et les graphiques 3D avancés. Cette innovation concerne nos produits phares - AutoCAD, Revit et Construction Cloud - ainsi que Forma, notre nouveau Cloud industriel.
En tant que développeur/ingénieur en apprentissage automatique au sein de l'équipe AEC Solutions, vous rejoindrez une équipe de technologues pour aider à construire des modèles de base et des outils d'IA générative pour l'industrie AEC. Vous travaillerez en collaboration pour créer et interpréter des données de conception qui peuvent améliorer les flux de travail de conception et d'ingénierie.
**Rapport :** Vous serez rattaché(e) au responsable de l'apprentissage automatique au sein de l'équipe des solutions pour l'architecture, l'ingénierie et la construction (AEC).
**Lieu de travail :** Nous soutenons le travail hybride, et vous travaillerez près de nos bureaux de Boston, Massachusetts ou Toronto, Canada.
**Responsabilités**
+ Architecte et guide dans la mise en œuvre de pipelines et d'architectures de données évolutives
+ Travailler avec des ensembles de données multimodales à grande échelle (texte, géométrie 2D/3D et données structurées), en développant des techniques avancées de prétraitement, d'augmentation et de compréhension du contenu
+ Architecturer, développer et optimiser des solutions de ML au niveau de la production, en se concentrant sur l'évolutivité et la fiabilité, tout en contribuant aux meilleures pratiques d'ingénierie
+ Établir les meilleures pratiques pour l'expérimentation, l'évaluation et l'optimisation des modèles
+ Contribuer à l'exécution technique en écrivant un code bien structuré et performant pour les pipelines de ML de production
+ Effectuer une analyse approfondie des besoins, collaborer avec les membres de l'équipe à différents niveaux et documenter les solutions
+ Vous définissez l'orientation technique en identifiant les principaux défis et en définissant des solutions innovantes
+ Vous communiquez efficacement les résultats techniques, en influençant les parties prenantes par des analyses quantitatives, des aperçus qualitatifs et des présentations visuelles claires
+ Encadrer et guider les ingénieurs débutants, en favorisant une culture de l'excellence technique et du partage des connaissances au sein de l'équipe
**Qualifications minimales**
+ Une maîtrise en apprentissage automatique, en intelligence artificielle, en mathématiques, en statistiques, en informatique ou dans un domaine connexe
+ Plus de 10 ans d'expérience en ingénierie de l'apprentissage automatique ou dans un domaine connexe, avec une expérience éprouvée en matière de leadership et de mise en œuvre pratique
+ Expertise dans les architectures d'apprentissage profond (par exemple, Transformers, CNN, GAN) et les cadres modernes d'apprentissage automatique (par exemple, PyTorch, Lightning, Ray)
+ Expérience des LLM et des technologies connexes, y compris les frameworks, les modèles d'intégration, les bases de données vectorielles et les systèmes RAG (Retrieval-Augmented Generation), dans des contextes de production
+ Compréhension approfondie de la modélisation des données, des architectures de systèmes et des techniques de traitement, y compris les représentations géométriques des données en 2D/3D
+ Expérience des services en nuage AWS et de SageMaker Studio pour le traitement évolutif des données et le développement de modèles
+ Solides bases en informatique, en calcul distribué et en efficacité algorithmique
+ Capacité avérée à traduire des concepts théoriques en solutions pratiques et en prototypes de mise en œuvre
+ Capacité à travailler de manière autonome tout en collaborant efficacement avec d'autres équipes, en comblant le fossé entre la recherche et la mise en œuvre pratique
+ Excellentes aptitudes à la rédaction technique et à la communication pour la documentation, les présentations et l'influence sur les équipes interfonctionnelles
**Qualifications souhaitées**
+ Expérience en architecture, ingénierie ou construction
+ Expérience approfondie de la préparation des données, de la sélection des hyperparamètres, des techniques d'accélération et des méthodes d'optimisation
+ Maîtrise des techniques de calcul parallèle et distribué, avec une expérience pratique de l'utilisation de plateformes telles que Spark, Ray ou des systèmes distribués similaires pour le traitement de données à grande échelle et l'apprentissage de modèles
+ Expérience confirmée dans le développement et le déploiement d'algorithmes d'apprentissage automatique à grande échelle dans des environnements de production
**Candidat idéal**
+ Vous êtes passionné par la résolution de problèmes pour les clients AEC (Architecture, Ingénierie et Construction) en appliquant des techniques d'apprentissage automatique
+ Vous êtes à l'aise pour faire avancer les choses dans des domaines nouveaux et ambigus où l'apprentissage et l'adaptabilité sont essentiels
+ Vous dirigez par l'action, en combinant leadership technique et mise en œuvre pratique
+ Vous collaborez facilement avec les autres et êtes à l'aise avec un minimum de directives
+ Vous vous efforcez constamment d'apprendre de nouvelles technologies et méthodologies
+ Vous cherchez des solutions innovantes à des problèmes techniques difficiles et vous développez rapidement vos idées
+ Vous n'avez pas peur d'expérimenter, de partager vos idées ouvertement et d'échouer rapidement
At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.
**Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers (Careers%20% %3E) .**

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
With over half a billion rides and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Trust & Safety, Growth and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business.
If you are a critical thinker with experience in machine learning workflows, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
As a machine learning engineer, you will be developing and launching the algorithms that power the platform's core services and impactful products. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, safety, personalization, and adaptive control. We are hiring motivated experts in each of these fields. We're looking for someone who is passionate about solving problems with data, building reliable ML systems, and is excited about working in a fast-paced, innovative, and collegial environment.
**Responsibilities:**
+ Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact
+ Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems
+ Develop statistical, machine learning, or optimization models
+ Write production quality code to launch machine learning models at scale
+ Evaluate machine learning systems against business goal
**Experience:**
+ B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
+ 5+ years of Machine Learning experience
+ Passion for building impactful machine learning models leveraging expertise in one or multiple fields.
+ Proficiency in Python, Golang, or other programming language
+ Excellent communication skills and fluency in English
+ Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, **reinforcement learning** , and multi-armed bandits
**Benefits:**
+ Extended health and dental coverage options, along with life insurance and disability benefits
+ Mental health benefits
+ Family building benefits
+ Child care and pet benefits
+ Access to a Lyft funded Health Care Savings Account
+ RRSP plan to help save for your future
+ In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
+ Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
+ Subsidized commuter benefits
Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $149,600 - CAD $187,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Job Description

Job Description

RQ09508 - Sr. Machine Learning Engineer

Downtown, Toronto

Hybrid: 3 Days onsite / 2 days remote

Contract (8+ months contract, possible extension)

Must-Haves:

• Deep Understanding of Machine Learning Concepts: Proficiency in fundamental machine learning concepts, algorithms, and techniques.
• Expertise in Natural Language Processing (NLP) : Knowledge of NLP techniques and models, especially BERT and other transformer-based models, for tasks like text classification, sentiment analysis, and language understanding.
• Experience with Deep Learning Frameworks: Proficiency in deep learning libraries such as TensorFlow or PyTorch . Experience with implementing, training, and fine-tuning BERT models using these frameworks is crucial.
• Data Preprocessing Skills: Ability to perform text preprocessing, tokenization, and understanding of word embeddings.
• Programming Skills: Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit-learn.
• Model Optimization and Tuning: Skills in optimizing model performance through hyperparameter tuning and understanding of trade-offs between model complexity and performance.
• Understanding of Transfer Learning: Knowledge of how to leverage pre-trained models like BERT for specific tasks and adapt them to custom datasets.

Nice-to-Have:

• Public Sector experience

RQ09508 - Sr. Machine Learning Engineer

Downtown, Toronto

Hybrid: 3 Days onsite / 2 days remote

Contract (8+ months contract, possible extension)

Must-Haves:

• Deep Understanding of Machine Learning Concepts: Proficiency in fundamental machine learning concepts, algorithms, and techniques.
• Expertise in Natural Language Processing (NLP) : Knowledge of NLP techniques and models, especially BERT and other transformer-based models, for tasks like text classification, sentiment analysis, and language understanding.
• Experience with Deep Learning Frameworks: Proficiency in deep learning libraries such as TensorFlow or PyTorch . Experience with implementing, training, and fine-tuning BERT models using these frameworks is crucial.
• Data Preprocessing Skills: Ability to perform text preprocessing, tokenization, and understanding of word embeddings.
• Programming Skills: Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit-learn.
• Model Optimization and Tuning: Skills in optimizing model performance through hyperparameter tuning and understanding of trade-offs between model complexity and performance.
• Understanding of Transfer Learning: Knowledge of how to leverage pre-trained models like BERT for specific tasks and adapt them to custom datasets.

Nice-to-Have:

• Public Sector experience