ML Engineer

Akkodis is seeking a ML Engineer for a contract position with a client in Toronto, ON (Hybrid). Ideally looking for experience with AI/ML, Fast API for API development, Cloud based AI/ML services such as AWS, GCP or Azure., SQL/NoSQL databases , PaLM 2 or Llama 2) Agile or Scrum and linux preference would be someone with the required skills and experience, particularly in large organizations.

Title: ML Engineer

Location: Toronto, ON

JD ML Engineer

As a ML Engineer, we're seeking a talented Python AI/ML Engineer with expertise in deploying ML models to handle production scale workloads, to join our AI driven product team. ML engineer is responsible for building/managing API’s for AI algorithms, introducing AI based innovations.

Mandatory Skills:

• Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent work experience).
• At least 3+ years of relevant experience as an ML Backend Engineer
• Practical experience in applying AI/ML driven technology solutions. Experience in Generative AI with a strong understanding of deep learning techniques such as GPT, VAE, and GANs is preferred.
• Experience in Fast API for API development, SQL/NoSQL databases and linux o.s.
• Up to date with LLM research and developing new features/products using LLMs (e.g. using PaLM 2 or Llama 2)
• Good experience with ML algorithms, Python, NLP, prior experience with backend design and web sockets
• Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice pattern
• Experience with Cloud based AI/ML services such as AWS, GCP or Azure.
• Understanding of ML/AI Pipeline & Development life cycle & tools, MLOps experience
• Good knowledge of software engineering practices like version control (GIT), DevOps (Azure DevOps preferred) and Agile or Scrum.
• Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.

Responsibilities:

• Design, develop, and maintain scalable and efficient backend services for ML model deployment and inference using FastAPI for our AI driven product.
• Implement various ML algorithms at scale e.g. time series forecasting, XGBoost, deep learning, NLP, etc. using GPUs clusters or Spark or Databricks or AWS Sagemaker or equivalent tools
• Coordinating with development teams and data scientists to determine application requirements and integration points.
• Understanding of fundamental design principles behind a scalable application and writing scalable code
• Implement security best practices to safeguard sensitive data and ensure compliance with privacy regulations
• Own and manage all phases of the software development lifecycle planning, design, implementation, deployment, and support.
• Build reusable, high-quality code and libraries for future use which are high performant and can be used across multiple projects.
• Work closely with data engineers and data scientists to integrate ML models into the production environment