Job Description

Role: Sr. Machine Learning Engineer, Generative AI Applications

Duration: 12 Months on C2C

Location: Remote, EST, can be US or Canada based

Experience: 15 Years

• Actively contribute to and re-use community best practices.

• Monitor, debug, track, and resolve production issues.

• Work with project managers to ensure that projects proceed on time and on budget.

• Collaborate with Technical Product Managers to ensure proper tracking of algorithmic performance KPIs and prioritize performance improvements based on effort and impact.

• Complete other responsibilities as assigned.

Required Skills and Qualifications:

• Minimum of seven years’ post-secondary education or relevant work experience

• Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline.

• Minimum of five years’ software development experience with Python and SQL.

• Minimum of three years’ experience building pipelines to deploy NLP and deep learning models into production in a cloud environment

• Minimum three years’ experience using PyTorch, Tensorflow, or MXNet, along with optimizing code for GPU clusters

• Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools

• Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications using tools such as NeMo

• Experience with various embedding models and setting up and tuning vector databases to improve performance of semantic search and retrieval systems

• Understand the underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs

• Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka; a Linux environment; (AWS).

• Knowledge of data pipeline and workflow management tools.

• Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation.

Thanks & Regards,

Additional Information

All your information will be kept confidential according to EEO guidelines.