About Reliant

We believe that making the best decisions means looking at all the facts – a near-impossible task in our era of information overload. To fix this, we are building the next generation of machine learning software. Powered by generative AI, our algorithms analyze key information sources and provide comprehensive, factual answers for even your most complex queries.

We believe that the transformative impact of generative AI will be only realized by those willing to take on the world’s biggest information challenges. To make this future come true, we deploy our longstanding expertise in reinforcement learning and natural language processing.

We are scientists. Builders. Entrepreneurs. We spearheaded many of AI’s most impactful applications. We led teams at Google, DeepMind, and EY Parthenon. We now bridge cutting-edge AI research and the biopharma industry.

About the role

We are looking for a Machine Learning engineer with a strong track record working on applied ML. Bonus points if you have worked in the life sciences. You’ll play a central role in defining and building our ML platform, enabling cutting-edge AI agents that excel at discovering and organizing knowledge. Your work will help lay the foundation for a  new way of working with data.

If you are passionate about applying AI to real-world problems, thrive in a fast-paced environment, and are excited about contributing to the growth of an ambitious startup, we’d love to hear from you.

What we’d love you to do (and love doing)

Your day to day work will mainly include building text based generative AI applications end-to-end with a strong focus on benchmarking and experimentation with models, prompts and system design. Also there are ample opportunities to dive deeper into topics, such as synthetic data generation, model distillation, training embedding models for retrieval, etc.

Am I a good fit?

Ask yourself the following questions:

• How does a transformer work?
• What is an embedding?
• What is a dataclass in Python?
• What is a quick way to share an interactive demo with colleagues?

If you find these questions straightforward and can explain at least three of the answers clearly, you’re likely a good fit for this role.

We’d love to see

• A Master’s degree in Computer Science, Physics, Mathematics, Engineering or a similar quantitative field — or equivalent practical experience. Bonus if you have NLP or reinforcement learning experience.
• Proven experience implementing practical ML algorithms and scaling them to millions of datapoints.
• 3+ years of experience developing in Python.
• Familiarity with at least one ML framework such as PyTorch, JAX, TensorFlow, or similar.
• Bonus: Experience applying AI to the life sciences or related fields.
• Bonus: Familiarity with cloud tooling around one or more of CI/CD, dockerization, model serving, data processing.

We’re hiring across experience levels, from junior to senior, and will calibrate the role and responsibilities based on your background and expertise.

What we offer

We’re building a high-impact, mission-driven company — and we want our team to share in that success. Here’s what we offer:

• An amazing team - work with curious, ambitious people who genuinely care about solving meaningful problems.
• Competitive Salary tailored to your experience and the role level.
• Equity / Stock Options — meaningful ownership in the company’s future.
• Generous Paid Time Off — including 27 vacation days.
• On-site Work Arrangements with Flexibility — on-site first culture with regular days for remote work.
• Learning & Development Budget — for books, courses, or conferences that help you grow.
• Fast Growth Environment — be part of shaping both the technology and the company from the ground up.
• Regular Team Retreats — we bring the team together at least once a year to collaborate and have fun.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.