AI/ML Engineer

We are seeking a highly skilled
AI Engineer
with strong expertise in building, deploying, and optimizing AI/ML solutions for production-grade applications. The ideal candidate should be proficient in LLMs, prompt engineering, AI automation, vector databases, computer vision, cloud services (AWS/Azure/GCP), and integrating AI into web/mobile applications.

You will work closely with our engineering, product, and design teams to develop intelligent features, automate workflows, improve system efficiency, and deliver AI-driven solutions to our global clients.

Key Responsibilities

1. AI/ML Development

• Design, build, and deploy AI models (LLMs, NLP, CV, predictive analytics).
• Fine-tune and optimize models using Hugging Face, OpenAI, Llama, etc.
• Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases (Pinecone, Chroma, Weaviate, Elastic).
• Build NLP-based features such as chatbots, summarizers, sentiment analysis, and automated document understanding.
• Work on computer vision tasks: OCR, object detection, blueprint analysis, anomaly detection, image classification. (Optional)

2. Backend & Integrations

• Develop and integrate AI services with backend APIs , Python – FastAPI/Django/Flask).
• Build scalable ML pipelines and microservices for inference.
• Integrate with third-party APIs (OpenAI, AWS AI, Azure Cognitive Services, Google Vision/VertexAI).
• Implement model monitoring, logging, and analytics for performance and accuracy tracking.

3. Prompt Engineering & Automation

• Design high-quality prompts for various use cases: legal, medical, e-commerce, LMS, chat automation, support agents, etc.
• Build agentic workflows using LangChain, LlamaIndex, or custom pipelines.
• Create automated workflows to classify data, parse documents, extract insights, or perform domain-specific actions.

4. Data Engineering

• Prepare, clean, and analyze datasets for training and inference.
• Work with structured and unstructured data (text, audio, image, video).
• Create embeddings, manage vector databases, and handle large datasets efficiently.

5. Cloud & DevOps

• Deploy AI models on AWS, Azure, GCP.
• Optimize inference cost and performance.
• Use Docker, Kubernetes for scalable deployments. (Optional)
• Implement CI/CD pipelines for AI services.

6. Collaboration & Documentation

• Work with PMs, designers, and clients to convert business requirements into AI solutions.
• Prepare clear documentation on system design, workflows, and AI pipelines.
• Support code reviews and mentor junior AI engineers.

Required Skills & Experience

Technical Skills

• Strong Python skills (PyTorch / TensorFlow / Transformers).
• Experience with LLMs: OpenAI GPT series, Llama, Mistral, Hugging Face models.
• Strong understanding of NLP, CV, and ML fundamentals.
• Experience with vector DBs (Pinecone, Chroma, Weaviate, Elasticsearch).
• Experience building RAG systems and agentic workflows.
• Experience with AWS AI (Comprehend, Bedrock), Google Vision, Azure OpenAI.
• Experience integrating AI with applications.
• Experience with microservices, REST APIs, webhooks, and event-driven systems.
• Experience with databases: MySQL, PostgreSQL, MongoDB.

Soft Skills

• Strong analytical and problem-solving mindset.
• Excellent communication and client-coordination skills.
• Ability to work in agile/sprint-based environments.
• Self-driven and proactive in researching new AI techniques.

Nice to Have

• Knowledge of speech-to-text/voice agents (Whisper, Twilio, Dialogflow).
• Experience with agent frameworks (AutoGen, CrewAI, LangGraph).
• Experience in healthcare, legal, finance, LMS, or e-commerce domains.
• Experience with MLOps: MLFlow, Weights & Biases.
• Ability to deliver end-to-end AI features independently.

Experience Required

3–7 years
of experience in AI/ML development

(or strong hands-on experience with LLMs and production AI systems).