Senior AI Data Engineer - GPSC Insights Engineering
General Motors3 days ago
Base Salary
$134k - $189k/yr
Responsibilities
- Own the architecture, design, development, and production delivery of scalable batch, streaming, and near-real-time data and AI engineering solutions.
- Assemble, curate, and transform structured, semi-structured, and unstructured data for training, validation, evaluation, feature generation, embedding generation, retrieval, and inference.
- Build source-system integrations from files, database extracts, APIs, event streams, external suppliers, and supply-chain systems.
- Develop reusable data products with data contracts, schema management, lineage, metadata, quality checks, and observability.
- Develop feature, embedding, and vector-retrieval pipelines for machine learning and generative AI applications.
- Build AI-enabled workflows using AI development frameworks, retrieval, evaluation, and workflow orchestration patterns.
- Establish MLOps and LLMOps patterns for versioning, experimentation, evaluation, deployment, monitoring, drift detection, and retraining.
- Lead architecture discussions, technology evaluations, tradeoff analysis, and technical decisions for complex problems.
- Improve processes, automation, infrastructure, and developer tooling to increase delivery speed and reduce operational risk.
- Partner with data scientists, ML engineers, product owners, business stakeholders, platform teams, cybersecurity, and governance teams.
- Resolve production issues, lead root-cause analysis, and implement preventative improvements.
- Mentor peers and junior engineers and raise engineering standards through design reviews, documentation, and knowledge sharing.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field, or equivalent experience.
- 6+ years of experience in data engineering, software engineering, platform engineering, or a related discipline.
- Strong proficiency in Python and SQL; Scala or another production programming language is a plus.
- Experience engineering data pipelines or platforms supporting machine learning, advanced analytics, or generative AI workloads.
- Experience with Apache Spark, Kubernetes, Kafka, cloud platforms, data architecture, data modeling, schema design, data contracts, and relational and non-relational data stores.
- Experience with CI/CD, infrastructure automation, testing, observability, incident response, and production support practices.
- Understanding of performance optimization, data quality, governance, metadata, lineage, privacy, access controls, and responsible AI data use.
- Experience with AI application frameworks or services such as LangChain, CrewAI, Vertex AI, or comparable technologies.
- Working knowledge of RAG, vector search, FastAPI, React application patterns, LLM evaluation, and agent orchestration.
- Preferred qualifications include a master’s degree, generative AI or LLM data pipeline experience, feature stores, model registries, experiment tracking, model serving, and MLOps/LLMOps capabilities.
- Preferred experience includes Databricks, Snowflake, Azure Machine Learning, MLflow, Hadoop, Hive, HBase, ADLS/S3, multimodal data, and automotive, manufacturing, supplier, or supply-chain domains.
- Strong collaboration, communication, influencing, and cross-functional leadership skills.
Benefits
- Hybrid work arrangement requiring attendance in Austin, Texas at least three times per week, or more frequently as business needs dictate.
- Potential eligibility for relocation benefits.
- Benefits include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings, sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance, employee assistance programs, and GM vehicle discounts.
- The role offers significant technical ownership, architecture influence, cross-functional impact, and mentorship opportunities.
Tech Stack
Apache HadoopApache HBaseApache HiveApache KafkaApache SparkAWSAzureDatabricksFastAPIGoogle Cloud PlatformKubernetesMLflowPythonReactScalaSnowflakeSQL
Categories
Data EngineeringML Engineering
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.