S&P Global - Senior Machine Learning Engineer (5-12 yrs)

As a Senior Machine Learning Engineer, you will have end-to-end ownership of the our Link application, driving its development and success. This role is perfect for you if you thrive on creating ML models and have a keen interest in the software engineering aspects of machine learning (MLOps).

You will :

Develop Advanced ML Models : Create innovative machine learning models to address complex business challenges and drive value.

Enhance Model Performance : Identify and resolve performance gaps in existing models with creative and effective solutions.

Leverage Unique Data : Work with proprietary unstructured and structured datasets, applying advanced NLP techniques to extract insights and build impactful solutions.

Optimize Application Scaling : Efficiently scale ML applications to maximize compute resource utilization and meet high customer demand.

Address Technical Debt : Proactively identify and propose solutions to reduce technical debt within the tech stack.

Drive the ML Lifecycle : Engage in all phases of the ML lifecycle, from problem framing and data exploration to model deployment and production monitoring, ensuring continuous improvement.

Collaborate Across Teams : Partner with cross-functional teams, including Data, Product Management, Design, and Engineering, to ensure smooth operations and contribute to the future product vision.

Technical Leadership : Oversee the development of core capabilities by scoping and planning ML projects effectively. Mentor and lead other ML Scientists and Engineers to help make our team even more awesome!

Enhance User Experiences : Collaborate with Product and Design teams to develop ML-based solutions that enhance user experiences and align with business goals.

Qualifications :

- Have 5+ years of significant, hands-on experience designing, building, evaluating, and maintaining robust and scalable production ML systems

- Excellent understanding of an ML-based product lifecycle

- Experience with scoping and planning of ML projects

- Comfortable with modern tools for building ML pipelines, including data processing, training, inference, and evaluation

- Proficiency in Programming languages like Python

- Demonstrated effective coding, documentation, collaboration, and communication habits.

- Strong problem-solving skills and a proactive approach to addressing challenges.

- Have led initiatives from the ideation stage to implementation

- Experience developing search or recommender systems

- Experience with modern LLM based Tech stack

- Experience working with databases and other datastores

Technologies We Use :

ML/Deep Learning : PyTorch, Transformers, HuggingFace, LangChain

Deployment : Airflow, Docker, Kubernetes, Jenkins, AWS

EDA/Visualization : Pandas, Matplotlib, Jupyter, Weights & Biases

Tools/Toolkits : DVC, MosaicML, NVIDIA NeMo, LabelBox

Techniques : RAG, Prompt Engineering, Information Retrieval, Data Embedding

Datastores: Postgres, OpenSearch, SQLite, S3