Sign upLog in

Machine Learning (MLOps) Engineer

Atrium

New York, NY

Apply
JOB DETAILS
SALARY
$140,000–$190,000 Per Year
SKILLS
Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Automation, Best Practices, Business Operations, Cloud Computing, Communication Skills, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Data Science, DevOps, Distributed Computing, Docker, Documentation, Finance, GPU (Graphics Processing Unit), Genetics, GitHub, Healthcare, Identify Issues, Information Technology & Information Systems, Interviewing Skills, Jenkins, Machine Learning, Microservices, Microsoft Windows Azure, Operational Strategy, Performance Analysis, Performance Modeling, Production Control, Production Machining, Production Systems, Python Programming/Scripting Language, Regulatory Compliance, Reimbursement, Scalable System Development, Short Messaging Service (SMS), Software Development, Software Engineering, Software as a Service (SaaS), System Operations, Systems Reliability, Team Player, Validation Testing
LOCATION
New York, NY
POSTED
Today
Client Overview:
Our client is a fast-growing technology-driven organization focused on building scalable AI and machine learning solutions that power business-critical applications. They are looking to add a Machine Learning (MLOps) Engineer to their team. Their teams work across cloud infrastructure, data engineering, software development, and AI/ML platforms to deliver innovative products in a collaborative and fast-paced environment. They invest heavily in modern cloud technologies, automation, and data-driven decision-making.

Salary/Hourly Rate:
$140k - $190k (Dependent on experience and technical expertise)

Position Overview:
Our client is seeking a highly skilled Machine Learning (MLOps) Engineer to support the deployment, automation, monitoring, and scalability of enterprise machine learning systems. This role will partner closely with Data Scientists, Software Engineers, DevOps teams, and business stakeholders to operationalize ML models in production environments. The ideal candidate has strong experience building CI/CD pipelines for ML workflows, managing cloud-native infrastructure, and supporting end-to-end machine learning lifecycle management.

Responsibilities of the Machine Learning (MLOps) Engineer:
  • Design, build, and maintain scalable MLOps platforms and infrastructure for machine learning model deployment and monitoring.
  • Develop and automate CI/CD pipelines for ML training, testing, validation, and production deployment.
  • Collaborate with Data Scientists and Engineering teams to productionize machine learning models and workflows.
  • Implement model versioning, experiment tracking, feature stores, and automated retraining pipelines.
  • Monitor model performance, drift detection, system reliability, and operational health across production environments.
  • Manage cloud infrastructure and containerized applications using Kubernetes, Docker, and Infrastructure-as-Code tools.
  • Optimize ML workflows for scalability, performance, security, and cost efficiency.
  • Support governance, compliance, and reproducibility standards for enterprise AI systems.
  • Troubleshoot infrastructure, deployment, and model performance issues across distributed systems.
  • Contribute to platform engineering best practices, automation strategies, and operational documentation.
Required Experience/Skills for the Machine Learning (MLOps) Engineer:
  • 4+ years of experience in Machine Learning Engineering, MLOps, DevOps, or Platform Engineering roles.
  • Strong experience deploying and managing ML models in production environments.
  • Hands-on expertise with Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience building CI/CD pipelines using tools such as GitHub Actions, Jenkins, GitLab CI, or ArgoCD.
  • Proficiency with Docker, Kubernetes, and container orchestration platforms.
  • Strong cloud experience with AWS, Azure, or Google Cloud Platform.
  • Experience with ML lifecycle and orchestration tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Airflow.
  • Familiarity with Infrastructure-as-Code tools, including Terraform or CloudFormation.
  • Strong understanding of distributed systems, APIs, microservices, and production monitoring.
  • Experience with logging and observability tools such as Prometheus, Grafana, Datadog, or ELK Stack.
  • Strong communication and cross-functional collaboration skills.
Preferred Experience/Skills for the Machine Learning (MLOps) Engineer:
  • Experience supporting Generative AI, LLMOps, or Agentic AI platforms.
  • Familiarity with vector databases, RAG pipelines, and AI orchestration frameworks.
  • Experience working in highly regulated environments such as finance, healthcare, or enterprise SaaS.
  • Knowledge of data engineering technologies such as Spark, Kafka, or Snowflake.
  • Exposure to GPU infrastructure and model optimization techniques.
  • Experience implementing security and governance controls for AI/ML systems.
  • Kubernetes certifications or cloud platform certifications are preferred.
Education Requirements:
  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, or a related technical field is required.
  • Master's degree is preferred.
Benefits:
  • Competitive salary and annual performance bonus.
  • Comprehensive medical, dental, and vision coverage.
  • 401(K) with company match.
  • Flexible PTO and paid holidays.
  • Hybrid work flexibility.
  • Professional development and certification reimbursement.
  • Employee wellness programs.
  • Access to cutting-edge AI/ML technologies and cloud platforms.
  • Collaborative and growth-oriented engineering culture.
About Atrium:What you do matters. Guided by our Applicant-Centric™ approach, we foster an environment of collaboration, high performance, and innovation where your talents are valued, and your achievements are celebrated. Join us and become part of an inclusive team committed to your growth and success.
By applying to this job, you agree to receive calls, AI-generated calls, text messages, and/or emails from Atrium and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to opt out on any message you receive. For more details, please review our Terms of Use and Privacy Policy .

As a woman-owned firm, we value diversity. We are an equal opportunity and affirmative action employer and will consider all applications without regard to race, sex (including gender, pregnancy, sexual orientation and gender identity), age, color, religion or creed, national origin or ancestry, veteran status, disability (physical or mental), genetic information, citizenship or any other characteristic protected by law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Candidates who apply for roles through the Atrium website will be added to our candidate pool and may be considered for additional roles of a similar title. Please contact us to request an accommodation.
EOE/M/F/D/V/SO

Position ID: 396655

About the Company

A

Atrium

Resume Resources

Free Resume TemplatesFree Resume Builder