AI/ML Engineer
At a glance
Mid-level Machine Learning Engineering role at Fa Ewjt Saasfaprod1. Noida · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI applications in Python and FastAPI, then shape LLM workflows from incoming data through inference and generated responses
- Use GCP services to run AI workloads, including Vertex AI, Cloud Run or Functions, BigQuery and Cloud Storage
- Improve LLM responses with prompt techniques, embeddings, vector search and RAG
- Connect AI systems to enterprise platforms and keep their data moving reliably through tested CI/CD deployments
- Apply orchestration frameworks to complex workflows and assess emerging AI tools for possible use
What you bring
- At least two years developing AI solutions, with particular experience using LLMs
- You can build APIs with Python and FastAPI and have hands-on experience with GCP services
- You have worked with vector databases and RAG, and can apply prompt engineering techniques
- You understand software engineering fundamentals and use Git and CI/CD practices
Who this fits
This mid-level role suits an engineer who has built LLM-based solutions and can work across APIs, cloud services and retrieval workflows. It is based in Noida, India, with a hybrid arrangement.
From the employer
Responsibilities
1. Build production-ready AI applications using Python and FastAPI.
2. Design LLM pipelines including data ingestion, inference, and response generation.
3. Leverage GCP tools like Vertex AI, Cloud Run/Functions, BigQuery, and Cloud Storage.
4. Apply advanced prompt engineering techniques to enhance LLM outputs.
5. Implement vector stores and embeddings for semantic search and RAG.
6. Use orchestration frameworks (e.g., LangChain, LangGraph, CrewAI) for complex workflows.
7. Integrate AI systems with enterprise platforms and maintain robust data flows.
8. Follow best practices in coding, testing, and deployment within CI/CD pipelines.
9. Continuously explore and recommend emerging tools and AI technologies.
1. 2+ years of experience developing AI solutions, especially with LLMs.
2. Proficient in Python and FastAPI for API development.
3. Hands-on experience with GCP services (Vertex AI, Cloud Run/Functions, etc.).
4. Strong prompt engineering skills (e.g., CoT, few-shot, instruction tuning).
5. Experience with vector databases and RAG systems.
6. Familiarity with LLM orchestration frameworks.
7. Solid understanding of software engineering fundamentals.
8. Proficient with Git and CI/CD practices
Preferred Qualifications
1. Bachelors or Masters in Computer Science
2. Experience with MLOps for model deployment and monitoring.
3. Knowledge of distributed systems and data processing.
4. Contributions to open-source projects or strong AI project portfolio.
5. Strong communication skills and ability to explain technical concepts clearly.