Compliance-Bengaluru-Associate-AI/ML Engineer
- Hyderabad, Telangana
- Permanent
- Full-time
- Access to vast amounts of structured and unstructured data to fuel your AI/ML models, including textual data suitable for LLM applications.
- The opportunity to work with the latest AI/ML technologies, including Large Language Models and cloud computing platforms.
- A collaborative environment where you can learn from and contribute to a team of experienced engineers and scientists.
- The chance to make a tangible impact on the firm's ability to manage risk and maintain its reputation.
- Develop and deploy AI/ML models, including those based on Large Language Models (LLMs), using large-scale structured and unstructured data, addressing complex and impactful business challenges.
- Design and build scalable infrastructure for machine learning, including feature engineering pipelines and model deployment frameworks optimized for LLMs.
- Develop, productionize, and maintain AI/ML models, ensuring their accuracy, reliability, and performance, with a focus on LLM-based solutions.
- Design and execute AI/ML experiments, iteratively tuning features, prompts, and modeling approaches to optimize model performance, and meticulously documenting findings and results, especially in the context of LLMs.
- Collaborate with ML researchers to accelerate the adoption of cutting-edge AI/ML techniques and models, with a focus on advancements in Large Language Models.
- Participate in code reviews and contribute to maintaining high code quality standards.
- Contribute to the design and implementation of AI/ML model monitoring and alerting systems.
- Work with stakeholders to understand their needs and translate them into technical requirements, with an emphasis on identifying opportunities for LLM-based solutions.
- A Bachelor's or Master's degree in Computer Science, or a similar field of study.
- 4+ years of hands-on experience with building scalable machine learning systems
- Solid coding skills and strong Computer Science fundamentals (algorithms, data structures, software design)
- Extensive experience with Machine Learning and Deep Learning toolkits (Tensorflow, PyTorch, Scikit-Learn, HuggingFace)
- Demonstrated experience with Large Language Models (LLMs), including model fine-tuning, prompt engineering, and evaluation techniques.
- Experience in architecting and deploying ML applications on cloud, including containerization (Docker, Kubernetes).
- Experience in working with distributed technologies like Scala, Pyspark, Iceberg, HDFS file formats (avro, parquet), AWS/ GCP, big data feature engineering.
- Experience in system design and evaluating the pros and cons of database choices, schema definition for data storage.
- Experience with Agentic Frameworks (e.g., Langchain, AutoGen) and their application to real-world problems.
- Experience with model interpretability techniques.
- Prior experience in code reviews/ architecture design for distributed systems.
- Experience with data governance and data quality principles.
- Familiarity with financial regulations and compliance requirements.