Logo for MDA Edge

Senior MLOps Engineer

MDA Edge

Role overview

Qualifications

  • 7+ years in MLOps, ML Engineering, or related roles
  • Proficient in using Databricks, Apache Spark, ML Flow, Unity Catalog, and feature stores
  • Expertise in deploying low-latency ML models and reinforcement learning solutions
  • Strong knowledge of Git workflows and CI/CD practices

Responsibilities

  • Build and maintain scalable ML infrastructure on Databricks
  • Design and implement frameworks for detecting data and model drift
  • Develop model calibration frameworks and establish versioning practices
  • Create automated frameworks for training, retraining, and validating ML models

About the company

MDA Edge logo

MDA Edge

Our objective is to establish an exceptional ecosystem by connecting individuals, technology, and prospects through the application of human intelligence.MDA Edge is a process-oriented company and our expertise lies in providing comprehensive Workforce Solutions, specifically focusing on Contingent Staffing, Bulk/Project Staffing, RPO/KPO/BPO, and Direct Hire services. We cater to a wide range of industries, including Infrastructure Consulting, Engineering Consulting, IT Consulting, Healthcare, Life Sciences, Pharmaceutical Consulting, Consumer Goods, Education, Transportation & Logistics, Media & Entertainment, Telecom, BFSI, Manufacturing, Utilities & Energies, and Corporate Recruitment. Moreover, we have developed a dedicated focus on Government Consulting.Our company prides itself on a meticulous approach, ensuring that we meet your specific needs. We have established a robust network of highly skilled professionals who are readily available to fulfill your requirements. With a strong commitment to excellence, we consistently deliver exceptional results for clients in India, Denmark, France, Germany, Ireland, Japan, Spain, Thailand, the USA, Canada and Mexico, with ongoing expansion efforts to serve more new regions in the near future.We consistently uphold the highest standards of quality by providing resources, time, and materials to design, implement, and support efficient operations for organizations. Our track record of measurable accomplishments demonstrates our commitment to cultivating a balanced work and societal ecosystem.Our continuous growth, successful customer engagements, and strong customer retention exemplify our achievements. Furthermore, our passion lies in streamlining complex business processes through the application of suitable technology, which has been integral to our success.We extend an invitation to join our dynamic workplace, offering rapid growth opportunities, excellent employee benefits, and a positive work-life balance.

Company details

Company typeScaleup
Company size201 - 500

Links

Website LinkedIn See all jobs

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

Job Summary: We seek a Senior ML Ops Engineer to play a critical role in operationalizing machine learning workflows that drive dynamic pricing and personalized consumer experiences. This position focuses on building robust ML infrastructure and frameworks, including drift detection, model calibration, versioning, and reinforcement learning orchestration. The ideal candidate will bring expertise in Databricks, Unity Catalog, and feature stores and a deep understanding of Git workflows, Databricks workflows, and automated ML training pipelines.
Qualifications:
  • 7+ years in MLOps, ML Engineering, or related roles, focusing on deploying and managing ML workflows in production environments. Hands-on experience building drift detection systems, model calibration frameworks, and robust monitoring tools for ML pipelines.
  • Proficient in using Databricks, Apace Spark, ML Flow, Unity Catalog, and feature stores.
  • Expertise in deploying and orchestrating low-latency ML models, including reinforcement learning solutions like Contextual Bandits and Q-learning.
  • Experience designing automated training pipelines for ML models, focusing on efficiency
  • Strong knowledge of Git workflows, CI/CD practices, and tools like GitLab or similar.
  • Proficiency in Python, SQL, and big data processing tools like Spark.
  • Familiarity with ML lifecycle tools such as MLflow, Kubeflow, and Airflow.
  • Strong understanding of model performance monitoring, drift detection, and retraining workflows.
Key Responsibilities
  • ML Infrastructure Development: Build and maintain scalable ML infrastructure on Databricks, leveraging Unity Catalog and feature stores to support model development and deployment.
  • Drift Detection Frameworks: Design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production.
  • Model Calibration & Versioning: Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle.
  • Low-Latency Orchestration: Design and optimize reinforcement learning (RL) orchestration pipelines, including Contextual Bandits, for real-time execution in low-latency environments.
  • Automated Training Pipelines: Create automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment.
  • CI/CD for ML: Implement CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems.
  • Collaboration: Work closely with ML Scientists to ship, deploy, and maintain models.
  • Monitoring & Optimization: Build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments.

Apply once. Then go straight to the hiring manager.

After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
Unlocked after you apply
·

Field Engineer (Solutions) Related jobs

IndiaField Engineer (Solutions)

Other jobs at MDA Edge

Premium

Reach out to the hiring manager directly.

Gain access to the contact details of the hiring managers who actually decide, and reach out to network with them directly. That, plus more when you upgrade:

  • Full match report with fit score and gaps
  • Career diagnostics on how recruiters read you
  • Curated company matches and warm intros
  • 48h early access to new roles

Cancel anytime.