Sr. AI/ML Developer

Key Responsibilities

• Team Leadership: Lead, guide, and mentor a team of AI/ML engineers and data scientists, fostering a collaborative, innovative, and productive work environment.
• Clean Code & Development: Write clean, maintainable, and error-free Python code for developing robust machine learning systems.
• Model Engineering: Efficiently design, build, and deploy machine learning models and end-to-end solutions.
• Cross-Functional Collaboration: Work closely with diverse technical teams to ensure timely and efficient delivery of AI/ML projects.
• Data Science Lifecycle: Implement end-to-end data science processes, including data preprocessing, exploratory analysis, modeling, evaluation, and deployment.
• Database Management: Work proficiently with SQL and NoSQL databases to manage and retrieve data effectively.
• API Development: Develop and integrate RESTful APIs using Python web frameworks (e.g., Flask, Django).
• Debugging & Optimization: Diagnose issues and optimize existing code for performance improvements.
• Agile Methodologies: Follow Agile/Scrum software development lifecycle practices consistently.
• LLM & RAG Implementation: Design, develop, fine-tune, and deploy AI models focusing on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
• Model Validation & Evaluation: Conduct training, validation, and evaluation experiments, refining models based on statistical analysis and performance metrics.
• Security & Compliance: Ensure that AI/ML solutions adhere to security best practices and data privacy regulations (e.g., GDPR). Technical Qualifications
• Python Expertise: 3–5 years of hands-on experience with Python programming.
• ML/DL Experience: 3–5 years of experience building, training, and deploying Machine Learning and Deep Learning models.
• Deep Learning Frameworks: Proficiency with TensorFlow, PyTorch, and Keras.
• Web Frameworks: Solid experience with Python web frameworks (Flask, Django) for API development.
• Core Libraries: Strong expertise in NumPy, Pandas, Matplotlib, Scikit-learn, SpaCy, NLTK, and HuggingFace Transformers.
• Algorithms & Techniques: Deep understanding of ML/DL algorithms, with advanced techniques in NLP and/or Computer Vision.
• Production-Grade AI: Proven experience designing and deploying AI solutions leveraging LLMs and RAG.
• NLP & Conversational AI: Hands-on expertise in text representation, semantic extraction, sentiment analysis, and conversational AI.
• Concurrency: Practical knowledge of multithreading, concurrency, and asynchronous programming in Python.
• Database Proficiency: Advanced skills in SQL (PostgreSQL, MySQL, SQLite, MariaDB) and NoSQL (MongoDB) databases.
• Deployment & MLOps: Experience with containerization (Docker/Kubernetes), cloud platforms (AWS, Azure, GCP), and familiarity with MLOps principles for CI/CD, monitoring, and logging.
• Version Control: Proficient understanding of Git and Bitbucket for software version control.
• C++: Experience with C++ development is a plus. Soft Skills
• Analytical Thinking: Strong analytical and structured problem-solving capabilities.
• Proactive Problem-Solving: Logical reasoning and a hands-on approach to debugging and optimization.
• Team Collaboration: Effective interpersonal skills to work seamlessly with cross-functional teams.
• Clear Communication: Excellent ability to articulate technical concepts to diverse audiences.
• Continuous Learning: Commitment to staying current on emerging trends in AI/ML, NLP, and Computer Vision.