[Hiring] AI/ML Engineer @ISHIR

Role Description

We are looking for a hands-on AI/ML Engineer to design, develop, and productionize machine learning and Generative AI solutions for real-world business use cases. The ideal candidate should have strong experience in Python, machine learning, deep learning, LLMs, RAG, and MLOps, along with recent hands-on experience delivering Generative AI solutions in production environments.

• Design, develop, train, fine-tune, and evaluate machine learning and LLM-based solutions.
• Build and maintain end-to-end ML/AI pipelines, covering data ingestion, processing, model development, inference, deployment, and monitoring.
• Develop and implement Generative AI applications, including LLM-powered solutions and RAG-based systems.
• Apply prompt engineering, context engineering, and LLM fine-tuning techniques to improve model performance and reliability.
• Design and implement solutions using vector databases, embeddings, and retrieval-augmented generation (RAG) architectures.
• Collaborate with Solution Architects, Data Scientists, and engineering teams to translate business requirements into scalable AI/ML solutions.
• Optimize models and AI applications for accuracy, latency, scalability, and cost efficiency.
• Implement model evaluation, guardrails, observability, and monitoring for production AI/ML systems.
• Follow MLOps best practices, including model versioning, CI/CD, deployment automation, and model lifecycle management.
• Stay current with emerging developments in Generative AI, LLMs, AI engineering, and machine learning technologies.

Qualifications

• 3–6 years of hands-on experience in Machine Learning Engineering or a closely related role.
• Strong proficiency in Python.
• Experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Hands-on experience with Generative AI and LLM-based applications.
• Experience with LLM fine-tuning, prompt engineering, and context engineering.
• Strong understanding of RAG architectures, embeddings, vector databases, and semantic search.
• Experience building and deploying production-grade ML/AI pipelines.
• Working knowledge of MLOps practices, including model versioning and CI/CD for machine learning workloads.
• Experience with at least one major cloud-based ML platform: AWS SageMaker, Azure Machine Learning, Google Cloud Vertex AI.
• Strong understanding of model evaluation, performance optimization, and production monitoring.
• Ability to work collaboratively with cross-functional technical teams and translate business requirements into practical AI/ML solutions.

Requirements

• Experience working on AI/ML solutions in regulated or highly sensitive domains, such as healthcare or government technology.
• Experience with multi-agent AI systems and orchestration frameworks.
• Experience with LLM evaluation frameworks and AI observability tools.
• Familiarity with containerization and cloud-native technologies such as Docker and Kubernetes.
• Experience working with APIs, microservices, and scalable AI application architectures.

What We're Looking For

• Strong hands-on engineering mindset with the ability to take AI/ML solutions from prototype to production.
• Practical experience solving real-world problems using Machine Learning and Generative AI.
• Ability to evaluate different models and approaches based on accuracy, performance, scalability, and cost.
• Strong problem-solving and communication skills.
• Ability to work effectively in a fast-paced, collaborative environment.