Description:

We are looking for Machine Learning Engineers who are passionate about building cutting-edge systems with LLMs and real-world data.
In this role, you will work closely with clients and teammates to design, prototype, and productize scalable machine learning solutions.
You will be part of a collaborative, high-performing team that values clear thinking, pragmatic execution, and continuous learning.
This position is ideal for individuals who thrive in fast-paced environments, enjoy tackling open-ended problems, and care deeply about the quality and impact of their work.

Requirements:

You must have expertise in LLM engineering, including familiarity with popular LLM providers and their best practices.
Experience building or working with agentic systems (e.g., tool use, memory, planning, multi-agent coordination) is a strong plus.
You should have a strong ability to rapidly prototype cutting-edge tools and research ideas, with a track record of turning prototypes into production-ready services.
Hands-on experience with statistics and machine learning is required, and you should be comfortable working with the Python ML stack: Pandas, Numpy, scikit-learn, XGBoost, PyTorch, etc.
Proficiency with development tools such as Git, Docker, SQL, Bash, and FastAPI is necessary.
A strong analytical mindset and business acumen are essential; you must be able to think critically about data and its impact on product or business outcomes.
A Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding is required.
Familiarity with AWS or Azure, GitHub Actions, Spark, Neo4j Cypher, and graph databases is a bonus.

We offer competitive compensation for this position.
Our company believes in accountability and does not practice micro-management, allowing for a more autonomous work environment.

Skills