Machine Learning Engineer, Co-op

About the role

Ancestry is a human-centered company dedicated to connecting people with their past. We are the global leader in family history, offering a vast collection of over 65 billion records, serving over 3.5 million subscribers, and having a DNA network of over 27 million people. Our commitment to location flexibility allows employees to work from home, in an office, or a hybrid of both, depending on the role and location.

Responsibilities

• Develop and deploy machine learning and large language models.
• Build and optimize AI agents to enhance automation and decision-making.
• Optimize model inference speed, storage efficiency, and scalability for real-world applications.
• Develop pipelines and MLOps workflows to streamline model training, evaluation, and deployment.
• Contribute to ML, LLMs, agent evaluation and monitoring platform.
• Experiment with new ML, LLM, and Agent technologies.

Requirements

• Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering or related quantitative field with a strong data focus.
• Proficient in Python and familiar with ML libraries such as TensorFlow, PyTorch or Scikit-learn.
• Experience with GenAI, LLMs, and agentic frameworks (LangChain, AutoGen).
• Strong problem-solving skills, with the ability to write clean, efficient, and scalable code.
• Strong written and verbal communication skills.
• Curiosity and go-getter attitude.
• Experience with cloud platforms, ML development tools, and ML deployment tools.
• Nice to have: Familiarity NodeJS or Java.
• Nice to have: Familiarity with LLM fine-tuning, retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, OpenSearch), LLM optimization, VLLM library, HuggingFace library or reinforcement learning techniques.

Qualifications

• Passionate about dedicating your work to enriching people’s lives.
• Part-time, work-study-based opportunity for active students in master's and PhD programs.

Skills

• Machine Learning
• Large Language Models
• Generative AI
• Agentic Frameworks
• Cloud Platforms
• MLOps
• Model Optimization
• AI Agents
• Vector Databases
• LLM Fine-Tuning
• RAG
• VLLM Library
• HuggingFace Library
• Reinforcement Learning

Benefits

• Location flexibility
• Equal Opportunity Employer
• Reasonable accommodations for qualified individuals with disabilities

Pay

• Details TBD

Schedule

• Part-time, work-study-based opportunity