Senior MLOps Engineer
TLDR
Design and scale scalable ML infrastructure and platforms, enabling autonomous ML workflows and production-grade deployments across a global product ecosystem.
- Design, evolve, and maintain scalable ML infrastructure, including Kubeflow, Feast, and Spark-on-Kubernetes environments.
- Build internal platforms, tools, and APIs that enable self-service ML development and deployment across distributed teams.
- Define and implement MLOps and LLMOps best practices, supporting the full lifecycle from experimentation to production.
- Collaborate with Data Science and engineering teams to standardize CI/CD, versioning, testing, and observability for ML workflows.
- Develop and optimize cloud-native solutions using AWS, Kubernetes, and infrastructure-as-code tools such as Terraform or Crossplane.
- Ensure seamless integration of ML artifacts into enterprise data catalog, privacy, and governance systems.
- Improve developer experience by creating reusable libraries, abstractions, and scalable orchestration frameworks.
- Partner cross-functionally to translate complex ML use cases into robust, production-ready platform solutions.
- Strong experience in DevOps and MLOps, including CI/CD pipelines, infrastructure as code, and observability systems.
- Hands-on expertise with Kubernetes, Kubeflow, Spark, and AWS cloud environments.
- Strong Python development skills, with experience building reusable libraries, APIs, and platform tooling.
- Proven ability to design and operate large-scale ML or data platforms in production environments.
- Experience working closely with Data Science teams to enable scalable ML workflows and deployment pipelines.
- Solid understanding of distributed systems and cloud-native architecture principles.
- Strong systems thinking mindset with the ability to balance platform standards and team autonomy.
- Excellent collaboration and communication skills in cross-functional engineering environments.
- Nice to have: experience with LLMOps, advanced ML orchestration, or data governance frameworks.
- Fully remote position within Brazil with flexible work arrangements.
- Comprehensive health, dental, and life insurance coverage.
- Flexible benefits program tailored to individual needs.
- Paid time off including vacation, additional annual days, and birthday leave.
- 100% paid parental leave with structured reintegration support.
- Wellness programs including fitness access, mental health support, and therapy sessions.
- Home office setup reimbursement and flexible scheduling options.
- Strong learning culture with career development programs and internal mobility opportunities.
- Inclusive, global work environment focused on collaboration, wellbeing, and innovation.
Requirements:
Benefits:
Benefits
Flexible Work Hours
Flexible benefits program tailored to individual needs.
Health Insurance
Comprehensive health, dental, and life insurance coverage.
Home Office Stipend
Home office setup reimbursement and flexible scheduling options.
Learning Budget
Strong learning culture with career development programs and internal mobility opportunities.
inclusive global work environment
Inclusive, global work environment focused on collaboration, wellbeing, and innovation.
Paid Parental Leave
100% paid parental leave with structured reintegration support.
Paid Time Off
Paid time off including vacation, additional annual days, and birthday leave.
Remote-Friendly
Fully remote position within Brazil with flexible work arrangements.
Wellness Stipend
Wellness programs including fitness access, mental health support, and therapy sessions.
Jobgether runs the largest remote job platform, effectively linking job seekers with over 200,000 flexible and remote opportunities that match their unique skills and preferences. Our focus is on enhancing the hiring process, ensuring efficiency while prioritizing the candidate experience, particularly in the growing health and wellness sector.
- Founded
- Founded 2020
- Employees
- 11-50 employees
- Industry
- Professional Services