Day-to-day as a ML Product Lead:

You will own the strategy and roadmap for Machine Learning Engineers at Layer6, working closely with tech leads, Layer 6 and AI/ML business and product leads, and our engineering partner leads.

• Engage analytics leads from different businesses, build relationship and gather priorities
• Effectively manage multiple machine learning (ML) workstream priorities, exercising judgement
• Communicate and opine with a product mindset, bring in experts as needed
• Coordination of a diverse set of stakeholders to put together product strategy
• Work with tech and product leads to develop and maintain roadmap, target state, and tradeoffs
• Owns our internal AI framework adoption from vision to backlog; identify new opportunity and prioritize features to define minimum viable releases; maximizing the value and the ROI of the MLE team
• Be an exceptional collaborator in a high-interaction environment
  

  ---

Job Requirements

What can you bring to TD? Tell us about your most relevant experience, credentials and knowledge for this role, as well as these essential requirements and attributes:

• Minimum three years of experience delivering major data science projects in large, complex organizations
• Strong communication, business acumen and stakeholder management competencies
• Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices
• Strong coding proficiency: python, R, SQL and / or Scala, cloud architecture a plus
• A track record of driving product adoption and growth
• Familiarity with cloud solution architecture, Azure a plus
• Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience a plus
• Master’s degree data science, artificial intelligence, computer science or equivalent experience

Key Responsibilities:

• Traditional ML:  Develop and deploy batch and real-time model inference pipelines to production, perform end-to-end integration testing.
• Gen AI: Develop and deploy scalable production Gen AI systems for Gen AI models. 
• Mode Serving Framework: Develop in house model serving framework or integrate open-source model serving framework with enterprise data platform.
• ML System Design: Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability.
• Data Analysis & Processing: Perform data analysis, data preprocessing, and feature engineering on complex and large datasets for machine learning models. 
• Model Deployment & Monitoring: Build and deploy model inference pipeline, ground truth pipeline, model monitoring pipeline to production environment. Continuously monitor production model performance and system performance
• Automation: Build CI/CD pipelines to automate model deployment, model deployment validation, model performance monitoring, and model retraining.
• Research: Stay up to date with the latest advancements in AI/ML technologies and apply them to improve existing ML systems or develop new systems and solutions.

• Technical Leadership: Provide technical expertise with a focus on efficiency, reliability, scalability, and security; includes planning, evaluating, recommending, designing, operationalizing, and supporting solutions in compliance with enterprise and industry standards.
• Collaboration: Work with machine learning scientists, product owners, data platform team and business partners to gather use case requirements and implement technical solutions for production AI/ML models.

Job Requirements:

Required Technical Qualifications:

• BSc+ in Computer Science, Math, Physics, or similar
• 2+ years of extensive programming experience, 1+ year experience of building machine learning production system
• Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models
• Experience with developing MLOps CI/CD pipelines for deploying AI/ML models
• Solid cloud experience with Azure or AWS and cloud AI/ML services such as Databricks, Kubernetes, docker and container orchestration, Azure Machine Learning, Azure Data Factory
• Strong experience with PySpark for big data processing and PyTorch for deep learning model serving
• Expert coder with Python, Java, or Scala
• Experience with RAG, LLM fine tuning, LLM serving
• Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting

Preferred Qualifications:

• Knowledge of cloud engineering 
• Self-motivated and demonstrated ability to take independent action to delivery results.
• Highly developed critical thinking, analytical and problem-solving skills
• Strong verbal and written communication skills, with the ability to work effectively across teams

As a Machine Learning Engineer, you will

• • Join a world-class team of AI developers with an extensive track record.
  • Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability.
  • Write clean, efficient, and maintainable code for ML models to ensure efficient deployment of scalable AI application.
  • Work with large-scale, real-world datasets that range from banking transactions, conversation histories, to large document collections.

Required Qualifications:

• • Master’s degree or equivalent work experience in Computer Science, Machine Learning, Statistics, Mathematics, Engineering or a related field
  • Strong background in machine learning and deep learning
  • 2+ years of extensive programming experience, 1+ year experience of building machine learning systems
  • Proven track record of applying machine learning to solve real-world problems

Preferred Qualifications:

• • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for ML model deployment and MLOps.
  • Familiarity with databases and SQL.
  • Experience with big data technologies (e.g., Spark).
  • Knowledge of deep learning concepts and frameworks.
  • Experience with data visualization tools and techniques.
  • Previous internship or project experience in machine learning or data science.

Benefits:

• • Entrepreneurial and inclusive culture
  • Excellent health coverage
  • Four weeks paid vacation
  • Catered lunches twice a week over machine learning and engineering reading groups
  • Opportunities to collaborate with faculty at the Vector Institute

As a Research Machine Learning Scientist, you will

• • Join a world-class team of machine learning researchers with an extensive track record in both academia and industry.
  • Research, develop, and apply new techniques in deep learning to advance our industry leading products.
  • Work with large-scale, real-world datasets that range from banking transactions, to large document collections.
  • Collaborate closely with our engineering team in a fast-paced startup environment and see your research deployed in production with very short turnaround.

Required Qualifications:

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field
• Strong background in machine learning and deep learning
• 2+ years of research experience with publication record
• Proven track record of applying machine learning to solve real-world problems

Preferred Qualifications:

• Depth of experience in relevant ML research disciplines
• Hands on experience in software systems development
• Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library
• Experience with Spark, SQL, or comparable database systems
• Experience using GPUs for accelerated deep learning training
• Familiarity with cloud computing systems like Azure or AWS

Benefits:

• Entrepreneurial and inclusive culture
• Excellent health coverage
• Four weeks paid vacation
• Catered lunches twice a week over machine learning talks
• Opportunities to collaborate with faculty at the Vector Institute