[BZA] Senior ML Platform Engineer - ML Platforms & MLOps

Reposted 24 Days Ago
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Hiring Remotely in Kraków, Małopolskie, POL
In-Office or Remote
Senior level
Software
The Role
The Senior ML Platform Engineer will design and scale machine learning platforms, support multiple POCs, collaborate with teams, and evaluate platform capabilities.
Summary Generated by Built In
Company Description

Software Mind develops solutions that make an impact for companies around the globe. Tech giants & unicorns, transformative projects, emerging technologies and limitless opportunities – these are a few words that describe an average day for us. Building cross-functional engineering teams that take ownership and crave more means we’re always on the lookout for talented people who bring passion and creativity to every project. Our culture embraces openness, acts with respect, shows grit & guts and combines employment with enjoyment.

Job Description

Project – the aim you’ll have
Our client is a leading e-commerce company specialized in fashion, shoes, accessories, beauty – i.e. retail / online fashion platform.
We are looking for an experienced Senior ML Platform Engineer to design, build, and scale machine learning platforms and MLOps tooling. You will work at the intersection of software engineering and machine learning, enabling teams to develop, deploy, and operate ML models reliably in production. You will join a team that values high engineering standards, automation, fast delivery of business value, and close collaboration with data science, product, and infrastructure teams.

Position – how you’ll contribute

  • Support and contribute hands-on to multiple ML platform POCs
  • Work closely with Applied Scientists, ML Engineers, and internal platform teams
  • Evaluate platform capabilities across:
  • GPU training and experimentation
  • Real-time and batch inference
  • Orchestration, monitoring, and operability
  • Multi-tenancy, isolation, and scalability
  • Assess integration points with existing in-house tooling
  • Perform performance and operability analysis
  • Contribute technical input to:
  • Build vs buy vs extend decisions
  • Target platform stack recommendations
  • OPEX and CAPEX justification for rollout

Qualifications

Expectations – the experience you need

  • 5+ years building and operating ML infrastructure or large-scale data/ML systems on cloud platforms
  • Experience supporting mission-critical systems serving multiple teams
  • Containers (Docker) and orchestration (Kubernetes)
  • Experience with streaming and batch processing systems (e.g. Kafka/Kinesis, Spark/Flink)
  • Experience designing and operating systems with strict latency and throughput requirements (e.g. systems with sub-10ms inference or retrieval paths)
  • Familiarity with caching, traffic shaping, and request management in production
  • Designing systems with SLOs, monitoring, and safe deployment practices
  • Experience with incident response, capacity planning, and post-incident reviews
  • Experience working with IAM, secrets management, and network boundaries
  • Ability to embed security, compliance, and governance into engineering workflows
  • Experience combining multiple platform components (open source and managed services) into a coherent, shared, multi-team, production-ready ML platform
  • Comfortable evaluating and integrating tools rather than relying on a single end-to-end solution
  • Evaluating build vs buy vs extend trade-offs
  • Clear articulation of technical trade-offs and recommendations
  • Ability to produce architecture designs, POC findings, and decision input
  • Effective collaboration with platform, infra, and ML teams

Additional skills – the edge you have

  • Experience with enterprise ML platforms (e.g. Databricks, Domino, ClearML)
  • Kubernetes-first ML systems
  • Hands-on experience running ML workloads on Kubernetes (EKS preferred)
  • Multi-tenant environments, resource isolation, autoscaling
  • Experience running and optimising GPU-based training workloads in shared, multi-tenant environments (e.g. scheduling, utilisation, cost efficiency).
  • Feature platform or feature store experience
  • Online/offline consistency, schema evolution
  • Familiarity with Hopsworks, Feast, or similar
  • Governance and compliance experience in regulated ML environments
  • Experience onboarding teams onto shared platforms
  • FinOps awareness (cost attribution and optimisation for ML workloads)
  • Developer experience / platform enablement mindset (golden paths, templates, onboarding flows)

Additional Information

Our offer – professional development, personal growth

  • Flexible employment and remote work
  • International projects with leading global clients 
  • International business trips  
  • Non-corporate atmosphere 
  • Language classes 
  • Internal & external training 
  • Private healthcare and insurance  
  • Multisport card 
  • Well-being initiatives 

Top Skills

Docker
Flink
Kafka
Kinesis
Kubernetes
Spark
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The Company
HQ: Cracow
1,000 Employees
Year Founded: 1999

What We Do

Software Mind is a global digital transformation partner with operations throughout Europe, the US and LATAM. Driven by tech and empowered by people, we provide companies with software engineers and autonomous, cross-functional development teams who manage software life cycles from ideation to release and beyond. For over 20 years we’ve been enriching organizations with the talent they need to boost scalability, drive dynamic growth and bring disruptive ideas to life. Our top-notch engineering teams combine ownership with leading technologies, including cloud, AI, data science and embedded software to accelerate digital transformations and boost software delivery. A culture, driven by trust, that embraces openness, craves more and acts with respect enables our experts to create evolutive solutions that support scale-ups, unicorns and enterprise-level companies around the world.

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