AI/ML Engineer

4 days ago


Pune, India Kreeda Labs Full time

Job Role: AI/ML Engineer Job Type: Permanent Full time Location: Pune (Hybrid) Notice Period: Immediate Joiners Experience: 1.5 - 4 years Job Description: We are seeking a highly skilled AI/ML Engineer with strong hands-on experience in Machine Learning, Deep Learning, and advanced GenAI solution development. The ideal candidate has built end-to-end ML/DL models, implemented GenAI systems (RAG, LLM orchestration), and deployed solutions at scale on cloud platforms. This role involves applying in-depth engineering principles, building scalable AI systems, experimenting with new GenAI technologies, and taking complete ownership of AI-driven initiatives.Key Responsibilities  Design, build, and deploy end-to-end ML and DL models for production use cases. Develop advanced GenAI solutions using Lang Chain, Lang Graph, Llama Index, vector databases (FAISS, Pinecone, Weaviate, etc.), and RAG-based architectures. Create Agentic AI workflows to automate reasoning and task execution. Build cloud-native AI pipelines (AWS/GCP/Azure), including model training, optimization, deployment, and monitoring. Work hands-on with data — sourcing, cleaning, preprocessing, and feature engineering. Develop backend components to integrate AI models with microservices and production systems. Rapidly prototype GenAI and ML features and convert research into deployable systems. Collaborate with engineering, product, and client teams to deliver reliable AI solutions. Continuously explore emerging ML/DL and GenAI technologies to improve internal capabilities. Experience & Qualifications  Must Have: 2–4 years hands-on experience in Machine Learning and Deep Learning projects. Proven track record of building and deploying ML/DL models in real-world applications. Strong expertise in GenAI ecosystems: Lang Chain Lang Graph RAG pipelines Vector databases Agentic AI workflows In-depth experience with Python, NumPy, Pandas, Scikit-learn, Py Torch or Tensor Flow Understanding of Transformers, LLMs, embeddings, and fine-tuning techniques. Solid knowledge of ML Ops practices (training pipelines, versioning, CI/CD for ML). Good to Have: Experience with Snowflake or similar data platforms. Advanced Computer Vision model development. Cloud deployment expertise (AWS/GCP/Azure). Strong mathematical foundation: statistics, linear algebra, optimization.


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