Senior AI/Machine Learning Engineer

Role & responsibilities

• Design, develop, deploy, and maintain scalable AI/ML solutions for production environments.
• Build, fine-tune, and optimize machine learning, deep learning, and Generative AI models to solve complex business problems.
• Develop and implement Large Language Model (LLM) applications using prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and vector databases.
• Design and optimize data pipelines, feature engineering workflows, and model training processes.
• Deploy and manage ML models using MLOps best practices, ensuring scalability, reliability, and performance.
• Collaborate with product managers, software engineers, data engineers, and business stakeholders to translate business requirements into AI-driven solutions.
• Evaluate model performance, conduct A/B testing, monitor production models, and implement continuous improvements.
• Develop APIs and integrate AI/ML models into enterprise applications and cloud-based systems.
• Ensure AI solutions adhere to security, governance, explainability, and responsible AI standards.
• Mentor junior engineers, conduct code reviews, and promote engineering best practices.
• Stay current with advancements in AI, machine learning, and Generative AI technologies and recommend innovative solutions.

Preferred candidate profile

• 5 to 10 years of experience in AI, Machine Learning, Data Science, or related fields.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, or a related discipline.
• Strong hands-on experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
• Proven experience building and deploying production-grade machine learning and Generative AI applications.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, LangChain, LlamaIndex, and vector databases.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform and MLOps tools including Docker, Kubernetes, MLflow, or Kubeflow.
• Strong understanding of machine learning algorithms, deep learning, NLP, and model optimization techniques.
• Experience developing REST APIs, microservices, and scalable distributed systems.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Ability to work independently in a fast-paced, collaborative environment and lead technical initiatives.
• Experience mentoring team members and driving technical excellence is highly desirable.