13 ml ops engineer jobs at 12 companies in Hackensack, NJ
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Senior ML Ops Engineer
New York, New York, United States
$210k-$300k/yrOnsiteFull Time
Confido: AI financial operations software for consumer packaged goods brands.
5+ YOE5+ years building production ML/ML platform systems, strong Python and cloud infrastructure skills, experience with IaC and CI/CD, productionizing models and agentic workloads, and ownership of reliability/observability.
Treeswift: Provides AI-augmented vegetation management and asset monitoring for utilities.
7+ YOE7+ years in observability/SRE/DevOps with Terraform, Kubernetes, Linux debugging, CI/CD, and cloud infrastructure; experience with Airflow/Astronomer and ML ops preferred.
San Francisco or Chicago or Scottsdale or New York
$118k-$203k/yrHybridFull Time
Early Warning Services: Operates payment and risk solutions for the financial industry.
5+ YOEBachelor's in CS/Engineering; 5+ years in Data Science/ML/Ops; Python; AWS; Docker/Kubernetes; MLflow/Kubeflow; real-time model deployment; strong data/compute systems knowledge.
BlackLineNASDAQ: BL: Provides cloud-based financial close and accounting automation software.
2+ YOE2+ years in Python/Java/Scala, experience building PySpark ETL, ML/LLM production pipelines, cloud (GCP/AWS/Azure), ML frameworks, orchestration, containerization, and observability.
New York City or Toronto or United States or Canada
$195k-$245k/yrRemoteFull Time, Contract
FutureFit AI: Provides AI-powered career navigation and workforce development software solutions.
Senior MLOps/data engineering experience with strong systems design, hands-on implementation of production data pipelines and ML workflows, fluency with modern data/ML stack and cloud infrastructure (SQL, Python, Airflow, dbt, AWS).
BlackLineNASDAQ: BL: Provides cloud-based financial close and accounting automation software.
Extensive experience building and operating ML/AI production systems, designing scalable data pipelines, distributed training, model deployment, CI/CD, observability, and cloud infrastructure.
The Walt Disney CompanyNYSE: DIS: Produces movies, operates theme parks, and provides streaming services.
5+ YOE5+ years in production ML engineering; strong CS/math background; backend microservices; cloud (AWS); data pipelines; ML Ops; leadership and collaboration.
8+ YOEPhD (8+ yrs) or MS (10+ yrs) in a relevant technical field; 8+ years designing, building, and deploying ML/DL/Gen-AI models; hands-on experience with production ML/LLM ops, scalable systems, and leading technical teams.
PepsiCoNASDAQ: PEP: Global manufacturer and distributor of snacks and beverages.
8+ YOESenior AI Engineer with 8+ years in software lifecycle, ML/AI, and production-grade agent systems; strong Python/Java, distributed systems, and ML Ops experience.
New York City or United States or Philadelphia or Boston
$199k-$241k/yrHybridFull Time
Veho: Provides AI-powered last-mile delivery services for e-commerce brands.
6+ YOEBachelor's degree plus 6+ years (or Master's plus 4+ years) in ML engineering; experience building ML platforms, training/serving infrastructure, feature stores, orchestration, monitoring, deployment pipelines; experience managing ML Platform/ML Ops teams; hands-on with Ray, Flink, Feast; cloud data tooling (AWS, Redshift, Databricks, Snowflake); s...
Ultra: Builds AI robots for automated warehouse order packaging and fulfillment.
Technical program management experience owning ML/robotics data programs, understanding of ML training data and evaluation, cross-team coordination with research/engineering/ops, and ability to drive delivery.
Vice President, Data Transfer, Integration & Quality Manager
London or New York
$69k-$175k/yrOnsiteFull Time
BNYNYSE: BK: Global institution managing and servicing financial assets worldwide.
Proven AI strategy and roadmap experience; hands-on with Python, ML/GenAI stacks, ML Ops/CI‑CD, cloud services and data pipelines; ability to translate business to technical plans; Bachelor’s in CS/Engineering/Mathematics required.
Python, ML Ops/CI‑CD, cloud services, data pipelines, monitoring/observability