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On Call Machine Learning Ops Engineer Jobs (NOW HIRING)

ML and ML Ops engineer Delaware or New Jersey( Report to work) Hybrid We are looking for a talented ... In this role, you will design, develop, and deploy machine learning models and large language ...

ML And ML Ops Engineer We are looking for a talented ML / LLM Engineer with deep expertise in AWS ... In this role, you will design, develop, and deploy machine learning models and large language ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior ML Ops Engineer

Norwalk, CT ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Overview Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow ...

Senior ML Ops Engineer

Philadelphia, PA ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior ML Ops Engineer

Philadelphia, PA ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior ML Ops Engineer

Philadelphia, PA ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

AI/ML Ops Engineer Location - Pleasanton CA (Onsite) Job Type - Contract We are looking for a ... machine learning model deployment and management. Key Responsibilities: * Design, build, and ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Overview LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the development of cutting-edge AI/ML solutions in collaboration with the Army's AI2C organization. This ...

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On Call Machine Learning Ops Engineer information

See salary details

$31.5K

$128.8K

$193.5K

How much do on call machine learning ops engineer jobs pay per year?

As of Jun 20, 2026, the average yearly pay for on call machine learning ops engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.
More about On Call Machine Learning Ops Engineer jobs
What cities are hiring for On Call Machine Learning Ops Engineer jobs? Cities with the most On Call Machine Learning Ops Engineer job openings:
What are the most commonly searched types of Machine Learning Ops Engineer jobs? The most popular types of Machine Learning Ops Engineer jobs are:
Infographic showing various On Call Machine Learning Ops Engineer job openings in the United States as of June 2026, with employment types broken down into 7% Locum Tenens, 3% As Needed, 64% Full Time, 18% Contract, 7% Nights, and 1% Summer. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Hiring: ML-Ops Engineer at Concord, CA

Realtech Services

Concord, CA โ€ข On-site

Contractor

Posted 7 days ago


Job description


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Job Title: ML-Ops Engineer

Location: Concord, CA (Onsite)

Duration: Long-Term Contract

Interview Process: Client Round โ€“ In-person (Lets Target only locals and willing to go for in-person interview at Clientโ€™s location)

Overview:

  • Tachyon Cortex Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions.

Key Responsibilities:

  • Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.
  • Automate model training, testing, deployment, and monitoring in cloud environments (e.g., GCP, AWS, Azure).
  • Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.
  • Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability)
  • Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs
  • Leverage Auto ML tools (e.g., Vertex AI Auto ML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment

Qualifications:

  • 10+ Years of professional experience in Software Engineering & 3+ Years in AIML, Machine Learning Model Operations.
  • Strong proficiency in Java andย  Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
  • Experience with cloud platforms and containerization (Docker, Kubernetes).
  • Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.
  • Solid understanding of software engineering principles and DevOps practices.
  • Ability to communicate complex technical concepts to non-technical stakeholders.
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