ChatGPT Jobs · 6 hours ago
Staff Machine Learning Engineer
United States
Full-time
Remote
Senior Level, Lead/Staff
$130K/yr - $260K/yr
5+ years expChatGPT Jobs is a company looking for a Staff Machine Learning Engineer to focus on end-to-end machine learning processes. The role involves working on ML platform architecture, defining standards for ML services, and leading design and implementation of models while collaborating with various teams to deliver ML capabilities.
Computer Software
Responsibilities
Work on the ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability
Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services
Lead design and implementation of models across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant)
Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real-world impact
Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies
Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and postmortems
Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs
Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence
Own build-vs-buy decisions and tooling/service selection (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles
Lead experienced engineers through complex platform implementations; drive system-wide architectural improvements and reliability practices
Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation and promote enterprise-wide ML standards
Where appropriate, collaborate on retrieval-augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems
Qualification
Required
Bachelor's degree or above in Computer Science, Engineering, Statistics, or related field
5+ years of professional software development experience using at least two general-purpose languages (e.g., Java, C++, Python, C#)
5+ years architecting, designing, and building multi-component ML platforms leveraging open-source/cloud-agnostic components: Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval), Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg, Streaming: Kafka; plus Flink/Spark Streaming experience, Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra), Distributed compute: Spark, Ray, Workflow orchestration: Airflow, Temporal
5+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support
5+ years working with cloud providers (Azure and/or AWS) in production ML contexts
Preferred
Experience leveraging or fine-tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims-facing tooling
Hands-on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing and online evaluation frameworks
Observability: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management
Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; familiarity with model risk management practices
Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship
Experience with high-throughput, low-latency inference and real-time feature pipelines
Company
ChatGPT Jobs
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2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase