- Company Name
- recruyt
- Job Title
- Machine Learning Engineer
- Job Description
-
Job Title: Machine Learning Engineer
Role Summary: Design, develop, and deploy scalable machine learning systems that power self‑learning applications. Drive end‑to‑end model life cycle—from data ingestion and feature engineering to experimentation, production deployment, and continuous improvement.
Expectations: Deliver production‑grade ML solutions within an early‑stage, high‑growth environment. Demonstrate ownership, rapid iteration, and ability to simplify complex problems.
Key Responsibilities:
- Build and maintain end‑to‑end ML pipelines using PyTorch and transformer‑based models.
- Deploy models on AWS infrastructure, ensuring scalability, reliability, and performance.
- Integrate Agentic AI frameworks (e.g., Langchain, MCP, A2A) and Retrieval‑Augmented Generation (RAG) systems into product workflows.
- Conduct data preprocessing, feature extraction, and statistical analysis on unstructured and structured data.
- Collaborate with React‑based product teams to embed ML features into the user interface.
- Monitor model performance, perform A/B testing, and retrain models to maintain accuracy.
- Document models, experiments, and deployment procedures.
Required Skills:
- 1–3+ years in a hypergrowth startup or similar high‑velocity environment.
- Proficient in PyTorch, transformer architectures, and modern ML frameworks.
- Hands‑on experience with AWS services for ML (SageMaker, Lambda, ECS/EKS, S3, CloudWatch).
- Familiarity with Agentic AI stacks (Langchain, MCP, A2A) and RAG pipelines.
- Strong ML fundamentals: recommender systems, embeddings, foundation models, and statistical methods.
- Production‑ready Python coding, version control, and CI/CD practices.
- Data engineering skills: scraping, parsing, cleaning, and transforming messy datasets.
- Basic understanding of frontend technologies (React) to enable seamless integration.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related field (or equivalent practical experience).