Software Engineer (AI/ML)

Job ID: 39582

Position Summary

AI/ML Engineer

Roles & Responsibilities:

• Design, develop, and deploy robust & scalable AI/ML models in Production environments.
• Collaborate with business stakeholders to identify AI/ML opportunities and define measurable success metrics.
• Design and build Retrieval-Augmented Generation (RAG) pipelines integrating vector stores, semantic search, and document parsing for domain-specific knowledge retrieval.
• Integrate Multimodal Conversational AI platforms (MCP) including voice, vision, and text to deliver rich user interactions.
• Drive innovation through PoCs, benchmarking, and experiments with emerging models and architectures.
• Optimize models for performance, latency and scalability.
• Build data pipelines and workflows to support model training and evaluation.
• Conduct research & experimentation on the state-of-the-art techniques (DL, NLP, Time series, CV)
• Partner with MLOps and DevOps teams to implement best practices in model monitoring, version and re-training.
• Lead code reviews, architecture discussions and mentor junior & peer engineers.
• Architect and implement end-to-end AI/ML pipelines, ensuring scalability and efficiency.
• Deploy models in cloud-based (AWS, Azure, GCP) or on-premises environments using tools like Docker, Kubernetes, TensorFlow Serving, or ONNX
• Ensure data integrity, quality, and preprocessing best practices for AI/ML model development.
• Ensure compliance with AI ethics guidelines, data privacy laws (GDPR, CCPA), and corporate AI governance.
• Work closely with data engineers, software developers, and domain experts to integrate AI into existing systems.
• Conduct AI/ML training sessions for internal teams to improve AI literacy within the organization.
• Strong analytical and problem solving mindset.

Technical Requirements:

• Strong expertise in AI/ML engineering and software development.
• Strong experience with RAG architecture, vector databases
• Proficiency in Python and hands-on experience in using ML frameworks (tensorflow, pytorch, scikit-learn, xgboost etc)
• Familiarity with MCPs like Google Dialogflow, Rasa, Amazon Lex, or custom-built agents using LLM orchestration.
• Cloud-based AI/ML experience (AWS Sagemaker, Azure ML, GCP Vertex AI, etc.).
• Solid understanding of AI/ML life cycle – Data preprocessing, feature engineering, model selection, training, validation and deployment.
• Experience in production grade ML systems (Model serving, APIs, Pipelines)
• Familiarity with Data engineering tools (SPARK, Kafka, Airflow etc)
• Strong knowledge of statistical modeling, NLP, CV, Recommendation systems, Anomaly detection and time series forecasting.
• Hands-on in Software engineering with knowledge of version control, testing & CI/CD
• Hands-on experience in deploying ML models in production using Docker, Kubernetes, TensorFlow Serving, ONNX, and MLflow.
• Experience in MLOps & CI/CD for ML pipelines, including monitoring, retraining, and model drift detection.
• Proficiency in scaling AI solutions in cloud environments (AWS, Azure & GCP).
• Experience in data preprocessing, feature engineering, and dimensionality reduction.
• Exposure to Data privacy, Compliance and Secure ML practices

Education and/or Experience:

• Graduation or master’s in computer science or information technology or AI/ML/Data science
• 3+ years of hands-on experience in AI/ML development/deployment and optimization
• Experience in leading AI/ML teams and mentoring junior engineers.