Job Type: Full-Time
Location: Remote
Experience: 7+ Years
English Proficiency: ADVANCED / FLUENT ENGLISH REQUIRED

We are seeking a highly experienced Senior AI/ML Engineer with strong hands-on expertise in Artificial Intelligence, Machine Learning, Large Language Models, Generative AI, and production-grade AI systems.

The ideal candidate must have extensive experience designing, developing, training, deploying, and optimizing AI/ML applications. We are looking for someone who is highly technical, comfortable writing code independently, and capable of explaining complex engineering concepts clearly during live technical interviews.

This is a hands-on engineering position requiring excellent programming skills, solid system architecture knowledge, and real-world experience building scalable AI solutions.

Key Responsibilities

- Design, develop, train, fine-tune, and deploy AI/ML models using Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Face Transformers.
- Build production-grade LLM applications, Generative AI solutions, and Retrieval-Augmented Generation (RAG) pipelines.
- Develop AI agents and multi-agent workflows using LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, and similar frameworks.
- Implement prompt engineering, function calling, tool calling, context management, and Model Context Protocol (MCP) integrations.
- Design semantic search and embedding pipelines using vector databases such as Milvus, Pinecone, pgvector, FAISS, and Weaviate.
- Build scalable backend services and AI APIs using Python, FastAPI, Flask, REST APIs, and asynchronous programming.
- Develop and maintain MLOps pipelines using MLflow, Airflow, Kubeflow, Docker, Kubernetes, and CI/CD.
- Deploy and optimize AI/ML workloads across AWS, Azure, and Google Cloud Platform.
- Implement model evaluation, experiment tracking, performance monitoring, drift detection, and automated testing.
- Optimize LLM inference, model latency, GPU utilization, and infrastructure costs.
- Work with SQL, PostgreSQL, Spark, Kafka, and large-scale data processing pipelines.
- Design distributed systems, microservices, and scalable cloud architectures.
- Troubleshoot production issues and improve AI system reliability, security, and performance.
- Collaborate with engineering teams and stakeholders to deliver AI solutions from initial development through production deployment.
- Participate in architecture reviews, technical discussions, and code reviews.

Required Technical Skills

- Programming: Python, SQL, JavaScript, TypeScript, Bash
- Machine Learning: PyTorch, TensorFlow, Scikit-learn, XGBoost, Hugging Face Transformers
- LLMs and Generative AI: OpenAI API,



Anthropic Claude, Llama, Mistral, AWS Bedrock, Azure OpenAI
- Agentic AI: LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, MCP, Tool Calling
- RAG and Vector Databases: Milvus, Pinecone, pgvector, FAISS, Weaviate, Chroma
- MLOps: MLflow, Airflow, Kubeflow, Ray, Docker, Kubernetes, CI/CD
- Cloud: AWS, Azure, GCP, SageMaker, Vertex AI, Azure Machine Learning
- Backend Development: FastAPI, Flask, REST APIs, Microservices
- Data Engineering: SQL, PostgreSQL, Spark, Kafka, Pandas, NumPy
- Monitoring and Evaluation: Prometheus, Grafana, LangSmith, Weights & Biases, Ragas

Candidates are not expected to know every tool listed, but must demonstrate deep hands-on experience with the core AI/ML technologies.

Mandatory Qualifications

- Minimum 7 years of professional software engineering, AI engineering, or machine learning experience.
- Strong hands-on Python programming experience.
- Proven experience developing and deploying AI/ML models into production.
- Strong understanding of LLMs, RAG, deep learning, and agentic workflows.
- Experience with cloud infrastructure, distributed systems, APIs, and MLOps.
- Ability to independently solve complex coding and architecture problems.
- Strong debugging, problem-solving, and analytical skills.
- Experience collaborating with technical teams and business stakeholders.

IMPORTANT: ENGLISH COMMUNICATION REQUIREMENTS

EXCELLENT SPOKEN AND WRITTEN ENGLISH IS MANDATORY.

Candidates must be able to communicate fluently, clearly, and confidently in English during technical interviews, team meetings, and discussions with stakeholders.

Applicants must demonstrate:

- ADVANCED OR FLUENT ENGLISH PROFICIENCY (C1 LEVEL PREFERRED).
- Excellent English listening comprehension and verbal communication.
- Clear, understandable pronunciation and the ability to explain technical concepts effectively.
- Ability to communicate technical decisions and reasoning in real time.
- Confidence participating in technical discussions entirely in English.

Candidates will be evaluated on communication clarity and comprehension, not on having a particular native or regional accent.

IMPORTANT: MANDATORY LIVE TECHNICAL INTERVIEWS





ALL CANDIDATES MUST BE COMFORTABLE COMPLETING LIVE CODING AND LIVE SYSTEM DESIGN INTERVIEWS IN ENGLISH.

Live Coding Interview

Candidates must demonstrate the ability to:

- Write working Python code in real time.
- Solve algorithmic and data structure problems.
- Implement APIs, data processing functions, and ML-related logic.
- Debug and optimize code during the interview.
- Explain their thought process clearly while coding.
- Discuss time complexity, scalability, and alternative solutions.

Live System Design Interview

Candidates must demonstrate the ability to:

- Design a scalable AI/ML system from scratch.
- Architect LLM applications, RAG pipelines, and AI agent workflows.
- Explain database selection, API architecture, caching, and distributed systems.
- Design cloud infrastructure and production deployment strategies.
- Discuss latency, scalability, security, reliability, and cost tradeoffs.
- Explain architectural decisions and answer follow-up questions confidently.

LIVE CODING AND LIVE SYSTEM DESIGN INTERVIEWS ARE REQUIRED PARTS OF THE HIRING PROCESS.

Candidates should be prepared to demonstrate their own technical skills without relying on AI coding assistants during the assessment unless explicitly permitted.

Preferred Qualifications

- Experience building enterprise-grade AI applications used by real customers.
- Experience with LLM fine-tuning, LoRA, QLoRA, and model optimization.
- Experience implementing multi-agent orchestration and autonomous AI workflows.
- Experience with NVIDIA GPUs, CUDA, TensorRT, or distributed model training.
- Experience with production LLM evaluation and observability.
- Strong background in software architecture and backend engineering.
- Previous experience leading technical projects or mentoring engineers.
- Experience working directly with enterprise customers.

Ideal Candidate

We are looking for a highly technical Senior AI/ML Engineer who can independently build production AI systems, write clean and efficient code, design scalable architectures, and communicate clearly in English.

The ideal candidate should be equally comfortable developing machine learning models, building LLM and agentic applications, deploying cloud infrastructure, debugging production systems, and completing challenging live technical interviews.

ONLY APPLY IF YOU HAVE STRONG HANDS-ON AI/ML EXPERIENCE, EXCELLENT ENGLISH COMMUNICATION SKILLS, AND ARE COMFORTABLE WITH LIVE CODING AND LIVE SYSTEM DESIGN INTERVIEWS.

Application Question(s):

- Do you have little to no accent?
- Can you work between 6:30pm - 2:30am Indian time (9am - 5pm EST)?

Language:

- English (Required)

Work Location: Remote

📌 Senior AI/ML Engineer (India)
🏢 hmunir
📍 India