Machine Learning Engineer (LLM Infrastructure) - Toronto
Toronto, Ontario, Canada
Prodigy Labs
Accelerating Digital Transformation Prodigy Labs provides a comprehensive range of expertise, from advisory services through to final delivery. We apply emerging technologies to enterprise client operations to create real, sustained value in...We are looking for a Machine Learning Engineer who has strong experience in building systems that accelerate the development and deployment of machine learning models, especially large language models (LLMs). You will partner closely with Machine Learning researchers and internal users to understand requirements and apply strong ML fundamentals to build high performance and reusable APIs and can also apply them in real production settings.
Please Note: This is a hybrid position and will require at least 2 days in the office per week. Successful candidates will need to complete a background check.
Responsibilities
- Architect/Enable distributed compute aligning workloads to Small/Mid/High end GPUs
- Leverage appropriate storage hardware and data formats to improve read/re-read efficiency
- Identify and remediate latency contributors especially IO bottlenecks, inefficient data shuffling, under/over utilized compute
- Scale models by employing distributed training using Data / Model Parallelism techniques
- Parallelize inference processing to improve prediction latency.
- Provide Subject Matter Expertise in Graph and Vector databases for various use cases including Knowledge Graphs, RAG etc.
- Implement LLM observability and monitoring solutions
- Manage infrastructure and large-scale system design and diagnose both model and system failures
- Mitigate reputation risk through AI driven Data Quality to ensure highest quality data and services are offered to clients
Requirements
- 5-6 years of AI, Big Data and cloud expertise
- 3-4 years of Alternative data experience
- 2+ years of experience building machine learning training pipelines or inference services in a production setting
- Experience with LLM deployment, fine tuning, training, prompt engineering, etc
- Experience with LLM inference latency optimization techniques, e.g. kernel fusion, quantization, dynamic batching, etc.
- Experience with CUDA, model compilers, and other model-specific optimizations
- Experience building, deploying, and monitoring complex microservice architectures.
- Degree in Computer Science or Engineering
- Prior Experience with: -Docker, Kubernetes, Infrastrure as code (Terraform)and containerization, Agile Methodology, Distributed systems, Databricks ML, Cloud (Azure (preferred) or AWS)
- Expert level – Python, SQL
- Experience (or knowledge of) Mosaic ML, Ray Framework
- Experience with Lang Chain or LlamaIndex
- Experience with any vector database
Nice to have
- Experience building front to back data pipelines comprising of data ingestion, enrichment, data quality, Analytics and reporting
- Experience with company KPIs and back testing of alternative data factors against company KPIs
- Experience with NLP techniques and transfer learning frameworks like BERT
- Experience with using HuggingFace Model Artifacts
Benefits
Why You'll Love Working at Prodigy
- We are a collective group of people and collaboration is key to our process
- We don’t work for our clients, we work with them
- A Flexible Hybrid Working Environment
- Easily accessible downtown location
- Competitive compensation commensurate with experience
- Everyone brings something valuable to the table in our supportive, challenging, and collaborative, diverse work environment
All Employees Can Participate in:
- Company paid health benefits: 100% medical, dental and vision coverage
- Corporate-discounted Gym Membership through GoodLife
- Company discount program including Travel, Shopping, Attractions, Wellness, & Sporting events, just to name a few
- Access to an Employee & Family Assistance program (EAP)
- Employee Referral Program
- Employee Opportunity Program
- Professional Development Program
- Town Halls
- Philanthropic Events
- Social Events
Accessibility
Prodigy is committed to providing equitable treatment and accommodation to ensure a barrier-free recruitment process and workplace. If you require accommodation at any stage during the recruitment process, please contact us at accessibility@prodigylabs.net or call 416-488-7700 ext. 4
Inclusion & Diversity
At Prodigy we foster an inclusive and diverse workforce, believing our strength stems from our individual differences. Our employees, partners, and clients continuously benefit from the innovation and creativity grounded in these values. We strive to be a company that attracts a diverse group of highly skilled people who know that their contributions will be valued and that they will be heard. We are committed to building a corporate culture with people who are excited to join our team, do their best work, and grow with us!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs Architecture AWS Azure BERT Big Data Computer Science CUDA Databricks Data pipelines Data quality Distributed Systems Docker Engineering HuggingFace KPIs Kubernetes LLMs Machine Learning ML models .NET NLP Pipelines Prompt engineering Python SQL Terraform Testing
Perks/benefits: Career development Competitive pay Fitness / gym Flex hours Health care Team events
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