Senior ML Operations Engineer
Belgrade, Serbia
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingMigrate training and inference workloads onto the ML platform with Data Science and AI teams
Implement model tracking, versioning and experiment management with MLflow
Build CI/CD pipelines for ML artifacts, including retraining triggers
Set up monitoring of GPU utilization, model latency and drift with Prometheus and Grafana
Build infrastructure for LLM workloads, including fine-tuning, vector databases and RAG
From the employer’s posting
migrate training/inference workloads onto the platform
Implement and maintain model tracking, versioning and experiment management (MLflow)
Build CI/CD pipelines purpose-built for ML/AI artifacts (model registries, container image pipelines, automated retraining triggers)
Establish monitoring and observability for ML/AI systems (Prometheus, Grafana) covering GPU utilization, model latency, throughput and custom ML metrics
Build and maintain infrastructure for LLM and generative AI workloads, including model fine-tuning pipelines, vector databases, RAG architectures and inference optimization
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience
- Hands-on experience with Spark, Docker and Kubernetes in production environments
- Experience building and operating end-to-end distributed systems
- Experience developing and maintaining ML systems built with open-source MLOps tools (e.g., MLflow, Argo, Metaflow, Airflow, Kubeflow)
- Strong understanding of software testing, benchmarking, and CI/CD practices
- Solid understanding of Linux systems administration
Qualification wording
Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience
Hands-on experience with Spark, Docker and Kubernetes in production environments
Experience building and operating end-to-end distributed systems
Experience developing and maintaining ML systems built with open-source MLOps tools (e.g., MLflow, Argo, Metaflow, Airflow, Kubeflow)
Strong understanding of software testing, benchmarking, and CI/CD practices
Solid understanding of Linux systems administration
Education & alternatives
Who You Are: - Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience - Strong software engineering skills in complex, distributed, multi-language systems (Python preferred)
Tools in this posting
- Python
- Docker
- Grafana
- Kubernetes
- MLflow
- Spark
- Airflow
Source — Tool mentions in context
What You'll Do: DeepIntent is seeking an MLOps Engineer to join our European Data Infrastructure team. The MLOps Engineer will partner with our Data Science and AI teams to build and scale a high-performance machine learning and AI platform spanning our on-prem data centers and GPU resources - built on Python, Spark, Kubernetes, Docker, and modern orchestration frameworks (Argo Workflows, Airflow). - Partner with Data Science and AI Engineering teams to adopt MLOps best practices and migrate training/inference workloads onto the platform
- Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience - Strong software engineering skills in complex, distributed, multi-language systems (Python preferred) - Hands-on experience with Spark, Docker and Kubernetes in production environments
- Strong software engineering skills in complex, distributed, multi-language systems (Python preferred) - Hands-on experience with Spark, Docker and Kubernetes in production environments - Experience building and operating end-to-end distributed systems
- Continuously improve platform reliability, cost-efficiency and maintainability of the underlying codebase - Establish monitoring and observability for ML/AI systems (Prometheus, Grafana) covering GPU utilization, model latency, throughput and custom ML metrics - Design and operate ML/AI deployment infrastructure, including GPU cluster architecture, model serving and tool selection across training and inference workloads
- Familiarity with LLM/generative AI tooling and concepts (model serving frameworks, embeddings, vector stores, RAG pipelines) is a strong plus - Familiarity with GPU infrastructure - CUDA fundamentals, GPU scheduling/orchestration in Kubernetes, and driver/toolkit management (NVIDIA drivers, CUDA toolkit, cuDNN) - Ability to work closely with data scientists and understand their tooling and workflows (Jupyter, notebooks, experiment tracking)
- Partner with Data Science and AI Engineering teams to adopt MLOps best practices and migrate training/inference workloads onto the platform - Implement and maintain model tracking, versioning and experiment management (MLflow) with observability into model performance and drift - Build CI/CD pipelines purpose-built for ML/AI artifacts (model registries, container image pipelines, automated retraining triggers)
- Experience building and operating end-to-end distributed systems - Experience developing and maintaining ML systems built with open-source MLOps tools (e.g., MLflow, Argo, Metaflow, Airflow, Kubeflow) - Strong understanding of software testing, benchmarking, and CI/CD practices
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 3, 2026 · 56 days ago
- Recorded sightings
- 28
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com.
What You'll Do:
DeepIntent is seeking an MLOps Engineer to join our European Data Infrastructure team. The MLOps Engineer will partner with our Data Science and AI teams to build and scale a high-performance machine learning and AI platform spanning our on-prem data centers and GPU resources - built on Python, Spark, Kubernetes, Docker, and modern orchestration frameworks (Argo Workflows, Airflow).
- Partner with Data Science and AI Engineering teams to adopt MLOps best practices and migrate training/inference workloads onto the platform
- Implement and maintain model tracking, versioning and experiment management (MLflow) with observability into model performance and drift
- Build CI/CD pipelines purpose-built for ML/AI artifacts (model registries, container image pipelines, automated retraining triggers)
- Continuously improve platform reliability, cost-efficiency and maintainability of the underlying codebase
- Establish monitoring and observability for ML/AI systems (Prometheus, Grafana) covering GPU utilization, model latency, throughput and custom ML metrics
- Design and operate ML/AI deployment infrastructure, including GPU cluster architecture, model serving and tool selection across training and inference workloads
- Build and maintain infrastructure for LLM and generative AI workloads, including model fine-tuning pipelines, vector databases, RAG architectures and inference optimization
- Collaborate with business units and Product on ML/AI-driven feature development
- Manage individual project priorities, deadlines and deliverables in a timely manner
Who You Are:
- Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience
- Strong software engineering skills in complex, distributed, multi-language systems (Python preferred)
- Hands-on experience with Spark, Docker and Kubernetes in production environments
- Experience building and operating end-to-end distributed systems
- Experience developing and maintaining ML systems built with open-source MLOps tools (e.g., MLflow, Argo, Metaflow, Airflow, Kubeflow)
- Strong understanding of software testing, benchmarking, and CI/CD practices
- Solid understanding of Linux systems administration
- Familiarity with LLM/generative AI tooling and concepts (model serving frameworks, embeddings, vector stores, RAG pipelines) is a strong plus
- Familiarity with GPU infrastructure - CUDA fundamentals, GPU scheduling/orchestration in Kubernetes, and driver/toolkit management (NVIDIA drivers, CUDA toolkit, cuDNN)
- Ability to work closely with data scientists and understand their tooling and workflows (Jupyter, notebooks, experiment tracking)
- An enthusiastic learner with a genuine thirst for keeping up with the fast-moving ML/AI infrastructure landscape
We believe great work starts with great support. That’s why DeepIntent offers a competitive, holistic benefits package designed to empower you both professionally and personally.
Here’s what you can expect when you join our team based in the US: Competitive base salary plus performance based bonus or commission, comprehensive medical, dental, and vision insurance, 401K match program, flexible PTO policy and paid holidays, remote friendly culture with flexible work options, career development and advanced education support, WFH and internet stipends, plus many more perks and benefits!
Here’s what you can expect when you join our team based in India: Competitive base salary plus performance based bonus, comprehensive medical insurance, and paid holidays. Hybrid-friendly culture with flexible work options, professional development reimbursement, WiFi reimbursement and health and wellness allowance plus many more perks and benefits!
Here's what you can expect when you join our team based in Europe: Competitive base salary plus performance-based bonus, comprehensive medical insurance, and flexible PTO. Hybrid-friendly culture with flexible work options, professional development reimbursement, WiFi reimbursement, and parental leave plus many more perks and benefits!
DeepIntent is committed to bringing together individuals from different backgrounds and perspectives. We strive to create an inclusive environment where everyone can thrive, feel a sense of belonging, and do great work together. DeepIntent is an Equal Opportunity Employer, providing equal employment and advancement opportunities to all individuals. We recruit, hire and promote into all job levels the most qualified applicants without regard to race, color, creed, national origin, religion, sex (including pregnancy, childbirth and related medical conditions), parental status, age, disability, genetic information, citizenship status, veteran status, gender identity or expression, transgender status, sexual orientation, marital, family or partnership status, political affiliation or activities, military service, immigration status, or any other status protected under applicable federal, state and local laws. If you have a disability or special need that requires accommodation, please let us know in advance. DeepIntent’s commitment to providing equal employment opportunities extends to all aspects of employment, including job assignment, compensation, discipline and access to benefits and training.
CCPA Notice: If you are a California resident applying for a role at DeepIntent, we may collect personal information as part of the application process in accordance with the California Consumer Privacy Act (CCPA). To learn more about the categories of information we collect and your rights, please contact PeopleOps@deepintent.com to see our full Applicant Privacy Notice.
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Belgrade, Serbia
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