Machine Learning Engineer, Co-op

United States Digital Space LLC; United States; Hybrid; USD 34,000 - 55,000; Part time

Job summary

the company seeks an exceptional Machine Learning Engineer Co-Op to join our MLE team this summer. You will develop and deploy ML models and LLMs, integrate GenAI features, and build AI agents to improve customer experiences and internal workflows.

This is a part-time, work-study-based opportunity for active master's and PhD students, offering collaboration with data scientists, engineers, and product teams to deliver scalable ML solutions.

Qualifications

• Pursuing advanced degree (Master's or PhD) in a quantitative field with strong data focus.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with GenAI, LLMs and agentic frameworks (LangChain, AutoGen).
• Great problem-solving, clean and scalable code, strong communication.

Responsibilities

• Develop and deploy machine learning models and large language models.
• Build and optimize AI agents to enhance automation and decision-making.
• Optimize model inference speed, storage, and scalability for real-world use.
• Develop pipelines and MLOps workflows for training, evaluation, and deployment.
• Contribute to ML/LLM evaluation and monitoring platforms.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

GenAI

LLMs

LangChain

AutoGen

Cloud platforms

Education

Master's or PhD in CS/DS/Statistics

Tools

LangChain

AutoGen

FAISS

Pinecone

HuggingFace

Job description

About the company:

When you join the company, you join a human-centered company where every person’s story is important. the company®, the global leader in family history, connects everyone with their past so they can discover, preserve, and share their unique family stories. With our unparalleled collection of more than 65 billion records, over 3.5 million subscribers, and over 27 million people in our growing DNA network, customers can discover their family story and gain a new level of understanding about their lives. Over the past 40 years, we’ve built trusted relationships with millions of people who have chosen us as the platform for discovering, preserving, and sharing the most important information about themselves and their families.

We are committed to our location flexible work approach, allowing you to choose to work in the nearest office, from your home, or a hybrid of both (subject to location restrictions and roles that are required to be in the office- ). We will continue to hire and promote beyond the boundaries of our office locations, to enable broadened possibilities for employee diversity.

Together, we work every day to foster a work environment that's inclusive as well as diverse, and where our people can be themselves. Every idea and perspective is valued so that our products and services reflect the global and diverse clients we serve.

the company encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants. Passionate about dedicating your work to enriching people’s lives? Join the curious.

the company seeks an exceptional, passionate, and highly motivated Machine Learning Engineer Co-Op to join our MLE team this summer. The MLE team is responsible for developing, deploying, fine‑tuning and optimizing machine learning models and LLMs to enhance customer experiences, improve internal workflows, and drive business impact. We collaborate closely with data scientists, engineers, and product teams to build scalable and efficient ML solutions that power critical features across our platform. As a Machine Learning Engineer Co-Op on the MLE team, you will work on integrating ML models and Generative AI (GenAI) models, enabling ML/LLM-powered applications, and developing AI agents using agentic frameworks. You will contribute to optimizing model inference, automating ML workflows, and building intelligent AI-driven solutions to improve decision-making and user engagement. This is a part-time, work-study-based opportunity for active students in master's and PhD programs.

What You Will Do:

• 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.

Who You Are:

• 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.

Additional Information:

the company is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, the company, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, the company will provide reasonable accommodations for qualified individuals with disabilities.

All job offers are contingent on a background check screen that complies with applicable law. For candidates who live in San Francisco, CA, pursuant to the San Francisco Fair Chance Ordinance, the company will consider for employment qualified applicants with arrest and conviction records.

the company is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at the company via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of the company. No fee will be paid in the event the candidate is hired by the company as a result of the referral or through other means.