Full-Time Associate Principal Engineer, Machine Learning

• Total experience 11+years.
• Strong working experience in machine learning, with a proven track record of delivering impactful solutions in NLP, machine vision, and AI.
• Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
• Strong understanding of statistical concepts and techniques, and experience applying them to real-world problems.
• Strong working experience in AWS.
• Strong programming skills in Python, and proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX, as well as machine learning libraries such as scikit-learn.
• Familiarity with MLOps tools such as MLflow, Kubeflow, Airflow.
• Proficient experience with Generative AI frameworks such as GANs, VAEs, prompt engineering, and retrieval-augmented generation (RAG), and the ability to apply them to real-world problems.
• Hands-on skills in data engineering and building robust ML pipelines.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
• Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

• Writing and reviewing great quality code.
• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementationWriting and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.

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