Data Scientist / Machine Learning Engineer (LLM & RAG Systems)

• Develop and optimize RAG pipelines to enhance LLM-driven troubleshooting.

• Work with PyVector to store and retrieve relevant data efficiently.

• Implement vector embedding models to power retrieval and improve accuracy.

• Build high-quality Python code to power our AI applications.

• Deploy and scale models on AWS (S3, Lambda, ECS, SageMaker, Bedrock).

• Fine-tune and evaluate LLMs for task-specific reasoning and accuracy.

• Implement efficient document indexing and retrieval for knowledge-intensive queries.

• Experiment, iterate, and deploy features quickly based on real customer feedback.

• Work with a small but highly skilled team to push the limits of industrial AI.

• Take ownership of challenges, figure things out as you go, and adapt to changing priorities.

• Strong Python development skills, with experience in machine learning or NLP.

• Experience with RAG architectures and knowledge retrieval techniques.

• Familiarity with PyVector for vector search and retrieval.

• Experience using vector embedding models (e.g., OpenAI, Bedrock Titan, Cohere, SentenceTransformers).

• Understanding of embedding models and best practices for retrieval.

• Experience working with AWS for cloud-based ML deployment.

• Knowledge of LangChain, LlamaIndex, or other RAG frameworks.

• Ability to work in a fast-paced, experimental environment, where iteration and adaptation are key.

• A self-starter who can work autonomously in a remote setting.

• A strong problem-solver who thrives when thrown in at the deep end.

• Work on cutting-edge AI in a complex and impactful industry.

• Be part of a small, agile, and highly talented team where your work truly matters.

• Enjoy full remote flexibility with the autonomy to shape your role.

• Build a product that solves real-world problems for top-tier industrial clients.

If this sounds like the kind of challenge you’re excited about, we’d love to hear from you. Apply now and help us build the future of AI-driven troubleshooting!

• We are owners: We get involved, understand the impacts we make and deliver what we commit to.
• We are bias for action: We take actions with a goal in mind and act fast
• We believe there’s always something to learn: We are not afraid of asking questions and learning from different people all the time
• We collaborate and communicate: We understand that team work is key and the team's success is also my success
• We support and respect each other: We support both external and internal stakeholders needs and respect differences we all have
• We stand by our values and walk the talk: We stand by our values to make sure that our culture is strong despite being remote-first

• Screening Interview with our HR Team
• Technical Interview with our Delivery Team
• Cultural Fit Interview with our Co-Founder