MLOps Engineer (Remote)
Joveo AI · Pune District, Maharashtra, India
- Hybrid
- Full-time
- $120,000 / year
- Pune District, Maharashtra, India
Job highlights
- Build and operate ML model production infrastructure.
- Ensure reliable, repeatable model deployment pipelines.
- Automate model retraining, validation, and deployment.
- Monitor deployed models for performance and drift.
- Collaborate with ML engineers and data scientists.
About the role
About Joveo
Every company says they're "AI-first." We actually are. Joveo's recruitment advertising platform processes millions of hiring decisions through machine learning, real-time bidding, and predictive analytics — helping the world's largest employers find the right people, faster and fairer. But we're not done. Not even close.Role: MLOps Engineer
Location: RemoteIndustry: Technology / AI & ML Infrastructure
Job Function: MLOps / ML Platform Engineering
Role Overview
We are hiring an MLOps Engineer to build and operate the infrastructure that takes Joveo's machine learning models from experiment to production reliably and repeatedly. You will be the backbone of our AI delivery pipeline — ensuring models are versioned, monitored, and deployed with the same rigour as our software systems.Key Responsibilities
- Build and maintain ML pipelines from training to deployment and monitoring
- Design model registries, experiment tracking, and feature store infrastructure
- Automate model retraining, validation, and deployment workflows
- Monitor deployed models for performance drift, data skew, and prediction quality
- Collaborate with ML engineers and data scientists to streamline the path to production
- Integrate ML infrastructure with CI/CD systems and cloud platforms
Required Skills & Qualifications
- Strong experience with ML platforms — MLflow, Kubeflow, SageMaker, or Vertex AI
- Proficiency in Python and infrastructure tooling (Docker, Kubernetes, Terraform)
- Experience building automated model training and deployment pipelines
- Familiarity with feature stores (Feast, Tecton, or Hopsworks)
- Understanding of model monitoring tools and drift detection approaches
- Strong DevOps/platform engineering fundamentals applied to the ML lifecycle
Equal Opportunity Employer
Joveo is an equal opportunity employer. We are committed to building an inclusive workplace and welcome applications from all qualified individuals regardless of race, color, ethnicity, nationality, gender, gender identity or expression, sexual orientation, age, religion, disability, marital status, or any other characteristic protected by applicable law. All hiring decisions are made solely on the basis of qualifications, skills, and demonstrated ability.If your dream job is one that doesn’t fit neatly into a job title — apply.Joveo. Where AI meets the future of work.
Key skills/competency
- MLOps Engineer
- Machine Learning
- Python
- Docker
- Kubernetes
- Terraform
- CI/CD
- Cloud Platforms
- Model Monitoring
- DevOps
Skills & topics
- MLOps Engineer
- Machine Learning
- Python
- Docker
- Kubernetes
- Terraform
- CI/CD
- Cloud Platforms
- Model Monitoring
- DevOps
- AI
- ML Platform
- Data Science
- Remote Job
How to get hired
- Tailor your resume: Highlight MLOps, ML platforms, Python, and CI/CD experience relevant to Joveo's needs.
- Showcase project experience: Detail your work on building and automating ML pipelines and production deployments.
- Quantify achievements: Use numbers to demonstrate the impact of your MLOps contributions.
- Prepare for technical questions: Brush up on Docker, Kubernetes, Terraform, and cloud ML platforms.
- Understand Joveo's mission: Research their AI-first approach and how MLOps enables their platform.
Technical preparation
Master Python for ML automation.,Practice Docker and Kubernetes for deployment.,Build ML pipelines with MLflow or Kubeflow.,Learn Terraform for infrastructure as code.
Behavioral questions
Describe a complex ML deployment challenge.,How do you monitor model performance drift?,Explain collaboration with data scientists.,How do you ensure pipeline reliability?
Frequently asked questions
- What are the key responsibilities for an MLOps Engineer at Joveo?
- As an MLOps Engineer at Joveo, you'll be responsible for building and maintaining the infrastructure that deploys and monitors machine learning models. This includes automating training and deployment, designing model registries and feature stores, and ensuring the reliability of our AI delivery pipeline.
- What ML platforms are used at Joveo for MLOps?
- Joveo values experience with ML platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI. Demonstrating proficiency in these or similar tools will be beneficial for an MLOps Engineer candidate.
- What programming languages and tools are essential for the MLOps Engineer role at Joveo?
- Proficiency in Python is required, along with experience in infrastructure tooling like Docker, Kubernetes, and Terraform. Familiarity with feature stores and model monitoring tools is also crucial.
- Is this MLOps Engineer position remote?
- Yes, the MLOps Engineer position at Joveo is a remote role, allowing you to work from anywhere.
- What kind of collaboration is expected for the MLOps Engineer role at Joveo?
- The MLOps Engineer will collaborate closely with ML engineers and data scientists to streamline the entire process of getting models from experimentation to production.
- How does Joveo utilize AI and ML in its operations?
- Joveo's recruitment advertising platform leverages machine learning, real-time bidding, and predictive analytics to process millions of hiring decisions, helping large employers find the right people efficiently and fairly.
- What is Joveo's stance on equal opportunity for MLOps Engineer applicants?
- Joveo is an equal opportunity employer committed to an inclusive workplace. They welcome applications from all qualified individuals and make hiring decisions based solely on qualifications, skills, and ability.