Machine Learning Engineer, Co-op

Benefits and culture

This part‑time co‑op role offers a human‑centered environment that values curiosity, growth, and real impact. You can work remotely with flexible location options, including from home, in an office, or a hybrid arrangement depending on location and role requirements. You will contribute to a data‑rich landscape with more than 65 billion records, over 3.5 million subscribers, and a growing DNA network with tens of millions of people, enabling meaningful improvements to customer experiences and internal workflows.

We prioritize inclusion and diverse perspectives, ensuring every idea is welcome and respected. The company supports location flexibility and is committed to equal opportunity for all applicants. Reasonable accommodations are provided for qualified individuals, and applicants from diverse backgrounds are encouraged to apply. It is our policy not to engage with unsolicited search firms for this opportunity; resumes submitted by search firms without a valid written agreement will be the property of the company, and no fees will be paid if a candidate is hired through other means.

What you will do

• Develop and deploy machine learning models and large language models to address real‑world needs.
• Design and refine AI agents to automate processes and strengthen decision‑making.
• Improve inference speed, storage efficiency, and scalability for production applications.
• Build pipelines and MLOps workflows to streamline training, evaluation, and deployment of models.
• Contribute to a platform for ML, LLMs, agent evaluation and monitoring.
• Experiment with new ML, LLM, and agent technologies to broaden capabilities.

Who you are

• Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering, or a 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 agent 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 a proactive, go‑getter attitude.
• Experience with cloud platforms, ML development tools, and ML deployment tools.
• Nice to have: familiarity with 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.

Technologies

• Python
• TensorFlow
• PyTorch
• Scikit‑learn
• LangChain
• AutoGen
• FAISS
• Pinecone
• OpenSearch
• VLLM
• HuggingFace
• NodeJS
• Java

About Ancestry

You will join a human‑centered organization where every person’s story matters. With a leadership position in family history, Ancestry connects people with their past to help them discover, preserve, and share their unique stories. The company offers a rich data ecosystem, a broad subscriber base, and extensive DNA networks, creating opportunities to influence products that touch millions of lives. Flexibility in work location, a commitment to inclusivity, and a culture that values diverse viewpoints are core to how we operate.

Additional information

Ancestry is an equal opportunity employer and makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender identity or expression, age, disability, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by law. Reasonable accommodations are provided to qualified applicants. Ancestry does not accept unsolicited resumes from search firms for this opportunity. Resumes submitted by search firms without a valid written agreement will be the property of Ancestry, and no fees will be paid if the candidate is hired through other means.