Antino Labs
AI/ML Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
25 September 2026
What they need
Job Description: We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertiseinGenerativeAI(GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownershipoftheAI lifecycle—from initial architectural design to final production execution. You will leadthedevelopmentof scalable AI-powered applications, demonstrating exceptional execution skills and theabilitytodeliverhigh-performance results under pressure in demanding production environments.
Machine Learning & LLM Capability:
End-to-End ML Engineering: Build and manage comprehensive ML pipelines, includingdataingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow,and Scikit-learn. Advanced LLM Systems: Design and implement sophisticated LLM-based applicationssuchasautonomous agents, chatbots, and complex automation tools. Generative AI Specialization: Architect and optimize Retrieval-AugmentedGeneration(RAG)pipelines using vector databases like FAISS, Pinecone, or Weaviate.
- Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning. Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as
2)LangChain or LlamaIndex. Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation. Project Ownership & Execution
- Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.
4)Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.
- Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.
6)Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.
7)System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.
8)Performance Under Pressure Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.
9)High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.
10)Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.
11)Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress. Qualifications: Bachelor’s or Master’s degree in Computer.
Qualification:
Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.
Proven expertise in Python, system design, and scalable AI/ML architecture.
Deep knowledge of NLP, Computer Vision, and Deep Learning models.
Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP,orAzure).
Pay: ₹2,000,000.00 - ₹4,500,000.00 per year
Benefits:
- Cell phone reimbursement
- Flexible schedule
- Health insurance
- Leave encashment
- Life insurance
- Paid sick time
- Provident Fund
Work Location: In person
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