(1071) Senior Machine Learning Ops Engineer

Explore the Nearsure experience!

🌐 Join our close-knit LATAM remote team: Connect through fun activities like coffee breaks, tech talks, and games with your team-mates and management.

🍃 Say goodbye to micromanagement! We champion autonomy, open communication, and respect for diversity as our core values.

⚖️Your well-being matters: Our People Care team is here from day one to support you with everything from time-off requests to wellness check-ins.

Plus, our Accounts Management team ensures smooth, effective client relationships, so you can focus on what you do best.

Ready to grow with us? 🚀

Here’s what we offer you by joining us!

✨ Competitive USD salary 💲 – We value your skills and contributions!

🌐 100% remote work 🏢 – While you can work from anywhere, you’re always welcome to connect with teammates and grow your network at our coworking spaces across LATAM!

💼 Paid time off – Take the time you need according to your country’s regulations, all while receiving your full salary. Rest, recharge, and come back stronger!

🎉 National Holidays celebrated 🌴 – Take time off to celebrate important events and traditions with loved ones, fully embracing your culture.

😷 Sick leave – Focus on your health without the stress. Take the necessary time to recover and feel better.

💸 Refundable Annual Credit – Spend it on the perks you love to enhance your work-life balance!

🤝 Team-building activities – Join us for coffee breaks, tech talks, and after-work gatherings to bond with your Nearsure family and feel part of our vibrant community.

🥳 Birthday day off 🎂 – Enjoy an extra day off during your birthday week to celebrate in style with friends and family!


About the project

As a Senior Machine Learning Ops Engineer, you will design and build large-scale architectures, workflows, tools, and automation for processing data and apply machine learning engineering to solve global business challenges with a focus on making tasks easier for data scientists.

How your day-to-day work will look like

✅ Architect and develop end-to-end machine learning solutions.
✅ Manage and automate the machine learning lifecycle.
✅ Collaborate with data engineers and data scientists to create highly scalable solutions.
✅ Work on cloud solutions, evaluating the performance and cost of potential architectures.
✅ Understand the software development life cycle to collaborate and integrate solutions with other technical areas.
✅ Interact with other teams to understand business challenges and propose solutions.
✅ Communicate and teach on how to use the developments.

This would make you the ideal candidate

✨ Bachelor's Degree in Computer Science, Engineering, or a related field.
✨ 5+ Years of experience implementing and deploying machine learning solutions in production environments.
✨ 5+ Years of advanced Python programming experience with hands-on experience in building robust, scalable, and testable ML pipelines.
✨ 3+ Years of experience working with SQL and Spark and distributed computing using Apache Spark.
✨ 3+ Years of experience working in cloud platforms, with practical expertise in AWS (especially SageMaker) and openness or prior exposure to GCP (supporting cloud migration efforts).
✨ Hands-on experience with Docker and containerized ML services, as well as orchestration tools such as Kubernetes or equivalents.
✨ Familiarity with ML model deployment via FastAPI, enabling real-time inference services.
✨ Experience with workflow orchestration tools like Airflow and familiarity with streaming processing frameworks such as Apache Flink for online feature calculation.
✨ Competence in infrastructure as code (IaC) using tools like AWS CloudFormation, with the flexibility to adapt to Terraform, supporting the team’s ongoing migration efforts.
✨ Solid understanding of time-windowed feature engineering for offline and online system.
✨ Knowledge of data architectures and systems integration.
✨ Proven track record in troubleshooting and optimizing complex ML and data systems.
✨ Experience automating machine learning lifecycles and managing end-to-end ML solutions.
✨ Scripting in Bash or equivalent environments for automation.
✨ Experience in building and integrating API endpoints for ML services, with API Management knowledge.
✨ Exposure to Feature Store concepts, and practical understanding of feature consistency between training and serving.
✨ Experience in vector databases and MLOps concepts related to serving and querying embeddings in production systems.
✨ Proactive and adaptable mindset; comfortable working in agile teams and contributing to technical architecture discussions.
✨ Experience in developing Proofs of Concept (PoC) and Proofs of Technology (PoT) in collaboration with research and innovation teams.
✨ Deep familiarity with the software development life cycle (SDLC) and collaboration with DevOps, Infra, and backend teams.
✨ Strong communication skills with the ability to explain complex technical solutions to both technical and non-technical stakeholders.
✨ Advanced English Level is required for this role as you will work with US clients. Effective communication in English is essential to deliver the best solutions to our clients and expand your horizons.

What to expect from our hiring process

1. Let’s chat about your experience!
2. Impress our recruiters, and you’ll move on to a technical interview with our top developers.
3. Nail that, and you’ll meet our client - your final step to joining our amazing team!

🎯 At Nearsure, we’re dedicated to solving complex business challenges through cutting-edge technology and we believe in the power of tailored solutions. Whether you are passionate about transforming businesses with Generative AI, building innovative software products, or implementing comprehensive enterprise platform solutions, we invite you to be part of our dynamic team!

We would love to hear from you if you are eager to make an impact and join a collaborative team that values creativity and expertise.

Let’s work together to shape the future of technology!

🧑‍💻 Apply now!