Job description
POSITION SUMMARY
WHAT YOU'LL DO WHAT YOU'LL DO Technology You participate in building, documenting, and refactoring production-grade AI/ML pipelines, model integration layers, and scalable features that grow with business needs. Process You identify and analyze areas in existing code, model inference workflows, and data pipelines for optimization, efficiency, and latency improvements.
Team You partner with product, design, data, and infrastructure teams to integrate AI/ML capabilities and intelligent services into application workflows. You participate in on-call support rotation for production ML services, if necessary. You actively participate in team meetings: sharing knowledge on emerging AI trends, asking questions, and challenging assumptions.
You actively help your team meet their commitments. You are open to constructive feedback from teammates and management. Personal You continuously improve your technical skills and stay current with rapid developments in the AI/ML landscape. Proven track record of writing maintainable code, including unit/integration tests, evaluation benchmarks, and readable code.
Expertise with learning new frameworks, algorithms, and technical stacks quickly. Familiarity with our tech stack: AI/ML & Data: Python, Py. Torch / Tensor. Flow, Hugging Face, Lang. Chain / Llama. Index, Vector DBs (e.g., Pinecone, Qdrant, pgvector) MLOps & Infrastructure: Docker, Kubernetes, MLflow / Weights & Biases, Cloud ML Platforms (AWS Sage.
Maker, GCP Vertex AI, etc.) Backend & API: Python, Go, Node.js, GraphQL, Elastic. Search, and Postgres WHAT YOU'LL NEED WHAT YOU NEED At least 3 years of professional experience building and deploying software systems, with direct experience integrating, fine-tuning, or operating AI/ML models in production environments.
Deep proficiency with Python and standard ML libraries (e.g., Py. Torch, Num. Py, Pandas, Scikit-learn, Hugging Face). Hands-on experience with LLMs, RAG architectures, prompt engineering, or traditional ML model pipelines and inference serving. Ability to design and implement robust APIs and backend microservices in Python (bonus if experienced with Go or Node.
js). Professional experience working with RDBMSs, NoSQL DBs, and Vector Databases. Demonstrated participation in the successful deployment, monitoring, and scaling of machine learning workloads and production code.