Software Data Engineer (Snowflake + AI/ML )

Primary Skills : Snowflake, AI/ML

Secondary Skills :PowerBi, AWS

Position Overview:

Software Data Engineer (Snowflake + AI/ML ) will be responsible for leading the design, analysis, and delivery of data-driven solutions to significant business challenges. This role involves working at a programmatic scale, coordinating delivery with multiple stakeholder teams. The team culture emphasizes collaboration, mutual support, and continuous learning. As an AI/ML Engineer, you will provide technical guidance and thought leadership for the team and the company as a whole. The team strives for excellence in the theory and practice of Machine Learning and encourages personal development and knowledge sharing.

Responsibilities:

• Lead, mentor, develop, and manage less-experienced members of the team to deliver key ML-powered features for our Marketing Analytics Platform.

• You will develop a program of work, partnering with stakeholders, to solve strategic business objectives across a range of horizons.

• Work on new use cases on the Application of Generative AI. • Translate business requirements and objectives into problems that can be solved with a combination of Data, Statistics, and Machine Learning.

• You will design and implement Machine Learning capabilities that improve Autodesk’s Marketing Data Platform. • You will perform statistical and data analysis and exploration to generate datasets for model training and development.

• Collaborate with other members of the team to reach better solutions, and to position our team at the cutting edge of technology and ML practice. Minimum Qualifications:

• Hands on experience in working with Marketing Domain datasets.

• 2+ years of applicable work experience in ML.

• 5+ years of hands-on experience in Snowflake.

• 2+ years of experience on Generative AI projects.

• Proficiency with the Python Machine Learning stack, e.g. Pandas, etc.

• Knowledge of experimental design and analysis of results.

• Demonstrate experience with applying Machine Learning, including both Deep Learning (PyTorch) and Classical ML (Scikit-Learn).

• Demonstrate experience with leading Machine Learning teams in deploying and improving ML features in production.

• Demonstrate experience working in cross-functional teams to deliver ML solutions at scale.

• Familiarity with Large Language Models, especially in the context of interactive dialog systems and chatbots (RAG, Generative AI, Conversational Agents).

• Experience deploying systems that use NLP such as Information Retrieval (IR), Recommender Systems (RecSys), or other NLP Applications. Preferred Qualifications:

• SQL and experience with big data technology such as Hive, Presto, Glue, (Py)Spark, or Athena.

• Advanced software engineering skills including data structures and algorithms.

• Experience with data pipelines and model serving in AWS.

• Experience with MLOps, especially on AWS, at scale.

• Experience working with AWS Cloud Formation templates is a plus.

• Familiarity with Agile and SCRUM methodologies is a plus.

• Experience working with PowerBI to develop dashboards is a plus.

• Analytical skills related to working with unstructured datasets.

• A successful history of processing value from large, disconnected datasets.

• Experience working with agile, globally distributed teams.