Build and deploy production-grade machine learning, deep learning, and Generative AI solutions. Responsibilities include developing models, RAG pipelines, AI agents, prompt engineering, data and training pipelines, scalable APIs, and MLOps practices. The role evaluates and optimizes model performance, cost, and latency while collaborating with product, data, and engineering teams to move AI capabilities from proof of concept to production.
About Techdome
Techdome Solutions Pvt. Ltd. is a technology consultancy and product engineering company founded in 2020 and headquartered in Indore. We design, build and run AI-powered, cloud-native platforms across data engineering, machine learning, cloud, automation, CRM and enterprise platforms. Our own products include JustInterview.ai and Catalyst ERP, and we serve clients from startups to large enterprises worldwide.
Why join us: work on global client programs and our own products, a fast-growing team, ownership from day one, and recognition as Madhya Pradesh Best Employer Brand 2026.
Job Details
Experience: 5–12 years
Notice Period: Immediate joiners only
Locations: Hyderabad, Indore, Noida, Delhi, Mumbai ,Remote
Employment Type: Full-time, permanent
Work Mode: Work from office
Education: B.E./B.Tech/MCA or equivalent in Computer Science, IT or a related field
How to Apply: Share your updated CV with current CTC, expected CTC and notice period / last working day.
We are looking for an AI/ML Engineer to build and deploy machine learning and Generative AI solutions, from model development to production-grade AI
applications.
Key Responsibilities:
- Design, train, evaluate and deploy ML and deep learning models for real business problems.
- Build Generative AI applications using LLMs, including RAG pipelines, AI agents, prompt engineering and fine-tuning.
- Work with frameworks such as LangChain, LlamaIndex and vector databases (Pinecone, FAISS, Weaviate, pgvector).
- Develop data preprocessing, feature engineering and model training pipelines.
- Deploy models as scalable APIs and services; set up MLOps practices for versioning, monitoring and retraining.
- Evaluate model performance, accuracy, latency and cost, and optimise accordingly.
- Work with product, data and engineering teams to take AI features from proof of concept to production.
Required Skills:
- 5+ years in ML/AI engineering or data science with production deployments.
- Strong Python with scikit-learn, PyTorch or TensorFlow.
- Hands-on experience with LLMs (OpenAI, Anthropic Claude, Llama, Mistral) and RAG architectures.
- Experience with NLP, computer vision or predictive modelling.
- MLOps tools such as MLflow, Kubeflow, SageMaker, Azure ML or Vertex AI.
- Experience with Docker, APIs (FastAPI/Flask) and cloud platforms.
Good to Have:
- Model fine-tuning (LoRA/PEFT) and LLM evaluation frameworks.
- Agentic AI frameworks (LangGraph, CrewAI, AutoGen) and MCP.
- Experience with Spark or Databricks for large-scale data.
- Publications, Kaggle work or open-source contributions.
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