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AI / ML Engineer (Data Science & Data Engineering – LLMs / GenAI)

AI / ML Engineer (Data Science & Data Engineering – LLMs / GenAI)

ReSun Technologies IncMumbai, IN
3 days ago
Job description

We are hiring a Senior AI / ML Engineer who brings strong experience across Data Science, Data Engineering, and Generative AI / LLM development . This role will work on end-to-end AI solutions — from building datasets and pipelines, to developing LLM applications, to deploying models in production.

Candidates may come from either a Data Scientist background, a Data Engineer background, or a hybrid AI / ML engineering background.

If you have strong experience with LLMs, Generative AI systems, data pipelines, or applied machine learning, we want to speak with you.

🔍 What You Will Do

LLM & Generative AI Development

  • Build, fine-tune, and evaluate LLMs for chatbots, agents, summarization, classification, and automation workflows
  • Design prompt engineering, prompt chaining, and RAG (retrieval-augmented generation) pipelines
  • Implement embeddings, vector search, and hybrid search workflows
  • Conduct model evaluation using quantitative and qualitative metrics
  • Prototype and ship applied AI solutions that solve real business problems

Machine Learning & Data Science

  • Perform data exploration, feature engineering, hypothesis testing, and modeling
  • Build predictive and classification models using modern ML techniques (transformers & classical ML)
  • Create datasets for model training, fine-tuning, and evaluation
  • Build dashboards, insights, and analytics to support product decisions
  • Data Engineering & ML Infrastructure

  • Build scalable ETL / ELT pipelines for ingestion, transformation, and model readiness
  • Integrate data from APIs, databases, cloud services, and unstructured sources
  • Prepare vectorization pipelines for RAG and LLM applications
  • Support deployment of AI / ML models using APIs, containers, and microservices
  • Develop monitoring, logging, CI / CD and automated workflows for stable production systems
  • Cloud, Storage & Performance

  • Work with Azure / AWS / GCP for storage, compute, and networking
  • Manage SQL / NoSQL databases, warehouses, and data lakes
  • Optimize pipelines, improve reliability, and ensure scalability
  • Maintain performance dashboards and observability tools
  • ⭐ Ideal Candidate Profile

    You may fit one (or more) of these backgrounds :

    Core Technical Skills

  • Strong Python programming skills
  • Strong SQL skills (data modeling, queries, optimization)
  • Experience with cloud platforms ( Azure preferred , AWS / GCP also welcome)
  • Experience with APIs, data ingestion, logs, and structured + unstructured data
  • Experience supporting large-scale AI / ML workloads and production systems
  • LLMs & Generative AI

  • Hands-on experience with OpenAI , Llama , HuggingFace , Anthropic , or similar LLM providers
  • Strong understanding of transformers, NLP fundamentals, embeddings, and tokenization
  • Experience with RAG , vector search, and embeddings
  • Familiarity with vector databases ( Pinecone , FAISS , Chroma , etc.)
  • Ability to design, evaluate, and optimize prompts and LLM workflows
  • Experience building chatbots, agents, summarizers, classifiers, or GenAI automation tools
  • Machine Learning & Statistical Foundations

  • Solid grounding in statistics , probability , and machine learning concepts
  • Experience building and validating ML models (traditional ML or deep learning)
  • Ability to evaluate model performance using quantitative and qualitative metrics
  • Experience preparing datasets for training, fine-tuning, and evaluation
  • Data Engineering & Pipelines

  • Experience building and maintaining ETL / ELT pipelines
  • Strong data modeling, schema design, and data quality practices
  • Experience integrating data from APIs, DBs, cloud systems, and external sources
  • Experience with pipelines for embeddings, vectorization, and model preparation
  • Familiarity with streaming / real-time systems (Kafka, EventHub) is a plus
  • ML Ops & Infrastructure

  • Familiarity with ML Ops tooling and workflows (CI / CD, testing, monitoring)
  • Experience deploying models via REST APIs, Docker, containers, or microservices
  • Ability to design stable, scalable, and reliable AI / ML infrastructure
  • Experience with GPUs, compute optimization, or distributed systems is a plus
  • End-to-End AI / ML Engineering

  • Comfortable working across both model development and data / infrastructure
  • Ability to design and deliver end-to-end solutions from ingestion → processing → model → deployment
  • Strong problem solver who can translate business needs into technical architectures
  • 🎯 Required Skills

  • 3–7+ years of experience in Data Science, Data Engineering, ML Engineering, or AI Engineering
  • Strong Python skills
  • Experience with LLMs, Generative AI, or ML modeling
  • Understanding of cloud environments (Azure / AWS / GCP)
  • Experience with SQL, APIs, and data modeling
  • Ability to turn business problems into technical architectures
  • ✨ Nice-to-Have

  • Experience fine-tuning LLMs (LoRA, QLoRA)
  • Experience deploying models on GPUs
  • Experience with Kubernetes, Docker, Terraform / Bicep
  • Familiarity with streaming systems (Kafka, EventHub)
  • Experience with multi-agent workflows
  • 📨 How to Apply

    If you're passionate about building real AI systems — not just prototypes — and want to work on impactful, production-grade solutions, we’d love to hear from you. Please share your resume at thowzif.abdullah@resunconsulting.com or apply here with your resume.

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