JOB DESCRIPTION

Sponsorship: GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.
Hybrid or Remote: This role is based remotely but if you live within a 50-mile radius of [Atlanta, Austin, Detroit, Warren, or Milford], you are expected to report to that location three times a week, at minimum.

YOUR SKILLS & ABILITIES

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
• 7+ years of experience in machine learning, engineering, data science, or a related field
• Candidate must be recognized as the SME or “go to” person for Machine Learning. You must have experience with many different forms of machine learning such as linear regression, decision trees, support vector machines, random forest, gradient boosting, PCA, CNN, LLMs and/or Generative AI. You must be able to use Machine Learning to solve complex problems in prior or current experiences and generally be considered a lead data scientist for AI/ML.
• Looking for Extensive Experience in the flowing:
• Programming & Frameworks : Python , R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL
• Machine Learning & AI : Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering
• Data Engineering : Databricks, Hadoop, SQL, Data Pipelines, Data Preprocessing & Feature Engineering
• Cloud & Big Data Platforms: (Preferred Microsoft Azure (Data Lake, Machine Learning, Databricks)), Nice to Have (AWS (S3, SageMaker, Bedrock) or Google Cloud Platform (BigQuery, Dataflow, AI Platform) )
• Deployment & MLOps: MLflow , Model Monitoring & Versioning, Docker & Kubernetes, GitHub , Jira
• Data Analysis & Visualization : Tableau, PowerBI, Pandas, NumPy
• Proven track record providing technical leadership in AI/ML
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment
• Strong problem-solving mindset and a proactive attitude towards learning and self-improvement

WHAT WILL GIVE YOU A COMPETITIVE EDGE (PREFERRED QUALIFICATIONS)

• Masters Degree in Computer Science, Engineering, Mathematics or related field
• Extensive NLP solutions from business problem statement to deployment and ongoing optimization
• Expertise with Large Language Models solutions from business problem statement to cloud deployment that have provided significant incremental business value
• Experience with generative AI solutions that you have developed and deployed into a production environment that have provided significant incremental business value
• Experience indirectly leading a team of data scientists to exceed customer expectations

THE ROLE

The Product Safety Data Analytics team is seeking a technical leader with an extensive hands-on experience in the full end to end data science lifecycle for artificial intelligence & machine learning.
This technical leader role requires extensive programming and statistical techniques to both solve complex problems and provide guidance to a team of data scientists that are focused on AI/ML.
If you’re passionate about driving innovation through AI/ML and are a proven technical leader, this role offers an exciting opportunity to contribute to impactful projects in a dynamic team environment.
As the Machine Learning Technical Lead, you will be responsible for working with our customers to understand their challenges and needs, develop new machine learning solutions, provide updates to existing production models, lead ML Ops in a cloud environment, develop proof of concepts for new generative AI solutions as well as providing technical expertise and guidance to a team of Data Scientists.

WHAT YOU’LL DO

• Train new machine learning models to solve complex business problems
• Enhance existing machine learning models to increase performance and adapt to our changing business landscape
• Prototype new AI solutions, including Generative AI, to solve business problems
• You provide guidance on business problems using statistical methods and can craft ad-hoc reports to share findings and recommendations with business partners
• Build statistical models that depict company-wide trends.
• Perform testing and validation of data sets
• Challenge of determining the meaning of data and explaining how various teams and leaders can leverage it to improve and streamline their processes
• Keeping defined structures in documentation and data and have a large toolset in statistical methodologies to tackle business problems