Layer 6 AI

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

Education Requirements:

• BSc+ in Computer Science, Math, Physics, or similar

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field

Experience Requirements:

• 3+ Years of industry experience as a Software Engineer leading the development of features

• Experience with building and scaling data-intensive software.

• 2+ years of research experience with publication record

• 2+ years of extensive programming experience, 1+ year experience of building machine learning production system

Other Requirements:

• Experience with building a library or a framework.

• Experience with Big Data technologies and frameworks including but not limited to Spark, Cassandra, Kafka.

• Experience with Microsoft Azure

• Comfortable with statistics.

• Knowledge of machine learning and deep learning.

• Knowledge of distributed systems.

• Strong background in machine learning and deep learning

• Proven track record of applying machine learning to solve real-world problems

• 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

• 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

• Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience

• Familiarity with cloud solution architecture, Azure a plus

• 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

• 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

Responsibilities:

• Own and ship product features that enable ML engine capabilities.

• Work with product owners and tech leads to design, ship, and refine significant components of the product.

• Work with scientists and MLOps teams to maintain and service the product.

• Translate broad business problems into sharp data science use cases, and craft use cases into product visions

• Own machine learning products from vision to backlog; prioritizing features and defining minimum viable releases; maximizing the value your products generate, and the ROI of your pod

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

Education Requirements:

• Master’s degree in data science, artificial intelligence, computer science or equivalent experience

Experience Requirements:

• Minimum three years of experience delivering major data science projects in large, complex organizations

Other Requirements:

• 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

• Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience

• Familiarity with cloud solution architecture, Azure a plus

Responsibilities:

• Translate broad business problems into sharp data science use cases, and craft use cases into product visions

• Own machine learning products from vision to backlog; prioritizing features and defining minimum viable releases; maximizing the value your products generate, and the ROI of your pod

• Guide Agile pods on continuous improvement, ensuring that the next sprint is delivered better than the previous

• Work closely with stakeholders to identify, refine and (occasionally) reject opportunities to build machine learning products; collaborate with support functions such as risk, technology, model risk management and incorporate interfacing features

• Facilitate the professional & technical development of your colleagues through mentorship and feedback

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

Education Requirements:

• BSc+ in Computer Science, Math, Physics, or similar

Experience Requirements:

• 2+ years of extensive programming experience, 1+ year experience of building machine learning production system

Other Requirements:

• 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

• 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

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.