Machine Learning Engineer

Key Responsibilities:

• 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.
  

Required Skills and Qualifications:

• 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 of development with the opensource machine learning and Generative AI stack like pytorch, keras, scikit-learn, langchain, llamaIndex, chromaDB, qdrant, SQL, MongoDB etc.
• Handson 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.
  

Preferred Skills and Qualifications:

• 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 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.