Development, and implementation of machine learning models and algorithms.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Preprocess and analyze large datasets to extract meaningful insights and patterns.
Conduct experiments to test hypotheses and evaluate the performance of different machine-learning approaches.
Implement and optimize machine learning pipelines for efficiency and scalability.
Deploy machine learning models into production environments and monitor their performance.
Document methodologies, processes, and results to ensure reproducibility and knowledge sharing.
Mentor and guide junior engineers and data scientists, fostering a collaborative and growth-oriented team culture.
Stay up to date with the latest advancements in machine learning and related technologies.
Requirements & Skills:
Master’s or Ph.D. degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
3-5 years of hands-on experience in machine learning, data analysis, or software development.
Strong fundamental knowledge of statistical modeling, machine learning, deep learning, Generative AI, natural language processing, computer vision, etc.
Proficient in programming languages such as Python and experience in development with opensource machine learning and Generative AI stacks like PyTorch, Keras, sci-kit-learn, long-chain, llamaIndex, chromaDB, qdrant, SQL, MongoDB, etc.
Hands-on with software development best practices, including version control (Git) and Agile methodologies.
Excellent problem-solving skills and ability to think critically and creatively.
Strong communication and presentation skills, with the ability to explain complex concepts to both technical and non-technical audiences.
Ability to work independently and as part of a team in a fast-paced, dynamic environment.
Experience with big data tools and platforms, such as Hadoop, Spark, or Hive
Experience with cloud computing platforms, such as AWS, Azure, or Google Cloud Platform
Experience with the latest technologies in natural language processing or computer vision or Generative AI (RAG, Agentic workflows, multi-modal models, etc)
Experience with developing use cases related to Conversational AI or Vision AI or AI enabled automation.
