Senior Machine Learning Engineer (Remote)

At EFG (ESL FACEIT Group) we create worlds beyond gameplay, where players and fans become a community. We pride ourselves in having a corporate social responsibility which is that “IT’S NOT GG, UNTIL IT’S GG FOR ALL”.

Our passion, craft, and DNA align to create and shape the world of esports, gaming tournaments, leagues, events, and holistic ecosystems through our millions of players, fans, and heroes, as well as through our people and culture.

We’re looking for an accomplished Senior Machine Learning Engineer who knows that the true mark of intelligence and experience is kindness, and the responsibility to use it to level up everyone around you.

You’ll be joining the ML Ops Team, whose mission is to design, build, and evolve a world-class ML Ops platform that empowers Data Scientists and delivers value to EFG's Business teams. This is a rare opportunity to shape the architecture and technical execution patterns of a greenfield ecosystem.

Expectations

Serve as a leader in tech

• Ask all the whys, relentlessly until you know your customer needs inside-out and know you’re designing the right solution to the problems and not the other way around;
• Partner with our stakeholders and serve as an internal consultant to foster the adoption of our data platform;
• You contribute to the technical strategy of the team, and its execution through prioritization, and delivery management;
• Set high standards across documentation, testing, resiliency, monitoring, and code quality. Enforce these standards by holding your team accountable;
• You drive towards efficiencies and look for ways to simplify code, infrastructure and data models across the platform;
• Inspire, teach and guide your fellow team members; lead design sessions, be there for a code review, take ownership of operational processes.

Excel as Senior Engineer

• Write well-rounded, reusable and documented code that captures the essential nature of the solution;
• Decompose ambiguous and open-ended problems into solutions composed of multiple tooling;
• Construct complex architectures tying multiple services and SaaS tooling together, leveraging a strong understanding of a cloud-based stack (GCP);
• Drive towards efficiencies, lowering our tech spend and tackling tech debt on a quarterly basis.

Personify our DNA

• Exemplify the values we live by. Nurture a blameless culture. Know and care for your team members; inspire, and guide them to be the best that they can be;
• Be the heart-first, people-first tech lead everyone wants to be around because you have invested in building relationships.

Requirements

MLOps & Infrastructure

• You are focused on building robust, scalable, and reproducible ML workflows;
• You’ve implemented CI/CD pipelines for ML systems with model versioning, automated evaluation, and deployment hooks;
• You deploy and maintain infrastructure as code using Terraform, provisioning ML workloads on GCP and Kubernetes;
• You’ve built serving systems enabling real-time inference for latency-critical applications;
• Your pipelines are observable and production-grade—wired into Prometheus, Grafana, and on-call tools like incident.io.

Architecture

• You’ve played a key role in architecting mature ML systems that deliver real business value—from real-time inference platforms to scalable retraining pipelines;
• You’ve led technical design and execution of system-wide improvements, such as migrating legacy workflows to modular, containerized, and versioned ML pipelines;
• You’ve run PoCs for new tools and frameworks (e.g., Seldon, LLM integration), evaluating them across scalability, maintainability, and performance dimensions;
• You’ve built and designed a platform that enables data science effectiveness based on ML lifecycle needs,  timely product deliveries and cross-functional stakeholder goals.

Machine Learning

• You work closely with data scientists and researchers, and you know how to translate prototypes into reliable production services;
• You’ve built and maintained models for classification, ranking, and embedding-based retrieval in PyTorch, with thoughtful evaluation and data validation workflows;
• You’ve integrated LLMs into systems—from prompt engineering to fine-tuning to serving—and understand their behavior in production;
• You care about model monitoring, drift detection, and making sure performance doesn’t degrade silently over time.

Engineering Hands-On

• You’ve supported the full lifecycle of ML —from experimentation to production deployment leveraging state of the art MLOps tools (e.g., MLFlow, Feast, Ray..io, Evidently.ai);
• You’ve built resilient batch pipelines with Airflow and dbt, and streaming data infrastructure with Pub/Sub to support near real-time use cases;
• You use Docker, Kubernetes, and FastAPI to build, containerize, and expose model services in production;
• You’re a master in Python, and apply the very best software engineering practices to pipeline design, testing, and performance optimization for scalable ML systems.

Tech Leadership

• You’ve served as a leader in technology in the past; you’ve made mistakes and learned from them;
• You have interacted with a large community of stakeholders before; you understand the business use cases and can tailor your communication to ICs and Senior Management.

Traits

• You like to have a good time while getting things done. When we say a “team player” we mean it - you have a crisp high-five and funny stories to tell. You have your team’s back, and the team has yours;
• You love learning new things: You know that there’s always more to learn. You’re up-to-date on new trends in data – you know who’s using what to solve various problems and are excited for the next release of your favorite tool;
• Past experience in the Esports/Gaming/Betting/Events industry would be a great asset;
• You make the time to cheer and enjoy the ride.