AI/ML Engineer

APM Terminals

5 - 10 years

10 - 15 Lacs

pune bengaluru

Posted:-1 days ago| Platform:

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Skills Required

supply chain deep learning usage gcp neural networks machine learning automation tools legal deployment python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Lead with autonomy: Take ownership of AI/ML projects from ideation to deployment, pushing boundaries of innovation.
Design the future: Develop and fine-tune Generative AI models (LLMs, diffusion models, GANs, VAEs, etc.) to optimize SCP business processes and enhance productivity.
Empower AI agents: Create agent AI architectures for autonomous decision-making, task delegation, and multi-agent collaboration using Agentic AI frameworks like AutoGPT.
Innovate with LLM s: Build & optimize LLM s applications, leveraging RAG and build robust Machine Learning pipelines for NLP, Multimodal AI tasks.
Work with cutting-edge tools: Harness the power of Vector Databases (e.g., Pinecone, FAISS, ChromaDB) and LLM APIs (OpenAI, Anthropic, Hugging Face, Mistral, Llama).
Collaborate for impact: Partner with cross-functional teams to integrate AI solutions into real-world applications like chatbots, copilots, automation tools, etc.).
Stay ahead: Perform continuous research on state-of-the-art AI methodologies, exploring advancements in Generative AI, Autonomous Agents, and NLP to drive innovation.

Required Skills & Qualifications [Must have]

Strong foundation in Machine Learning & Deep Learning with expertise in neural networks, optimization techniques and model evaluation.
Experience with LLMs, Transformer architectures (BERT, GPT, LLaMA, Mistral, Claude, Gemini, etc.).
Proficiency in Python, LangChain, Hugging Face transformers, MLOps.
Experience with Reinforcement Learning and multi-agent systems for decision-making in dynamic environments.
Knowledge of multimodal AI (integrating text, image, other data modalities into unified models.

Nice-to-have skills

Experience with Prompt Engineering, Fine-tuning, and RAG techniques.
Familiarity with Cloud Platforms (AWS, GCP, Azure) and deployment tools like Docker, Kubernetes, FastAPI, or Flask.

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