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Bloomreach

Senior AI/ML Engineer

Bloomreach is hiring a Senior AI/ML Engineer . Level rates it ; you can apply on Bloomreach.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include Vertex AI, MLflow and Databricks.
  • Level classifies it as a senior role.
  • Level lists 73 other open roles at Bloomreach.

AI in this role

vertex-aimlflowdatabricks
ai-agentsml-ops
Bloomreach is building the world’s premier agentic platform for personalization.We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey.
  • We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses.
  • We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey.
  • We're designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do.
And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora.

You'd be joining the Artificial Intelligence team. We own the algorithmic core of the platform: Predictions, Contextual Personalization, contextual bandits, autosegmentation, and the agentic workflows behind Loomi. We work with behavioural data at terabyte scale, across 1,400+ customers, in production, every day. You'll work on cutting-edge technologies, impacting millions of users, and contributing to a product that truly makes a difference. Working in one of our Central European offices (Bratislava, Brno, Prague) or from home (Czechia, Slovakia) on a full-time basis, you´ll become a core part of the Engineering Team.

The mission

You turn a model that works in an experiment into a service that works for 1,400 customers. You own ML-powered features end to end — the API that configures them, the pipeline that trains them, the endpoint that serves them, and the monitoring that tells you when they've drifted. That includes L3 escalations on what you ship. We think engineers who never see a production incident build worse systems.

What you'll actually do

  • Own features end to end — back-office APIs, training and inference pipelines, high-performance serving endpoints, monitoring.
  • Take models from the modelling side and make them production-grade. Usually that means rewriting the training path, thinking hard about feature freshness, and finding out what a model does with inputs nobody anticipated.
  • Design for the scale we actually run at — terabytes of behavioural data, multi-tenant, with latency budgets that make the naive approach unworkable.
  • Build the quality gates — unit and integration tests, shadow deployments, A/B testing, drift and performance alerting. Noticing a model has quietly degraded is your problem.
  • Support what you ship, including L3 investigations with our client-facing colleagues.
  • Write things down — design docs, runbooks, decision records. The team is growing and undocumented systems don't scale with it.

This role bends in three directions

We'd rather shape it around you than the other way round.

  • ML product engineering — you own an ML-powered feature end to end and the ML part is what makes it interesting.
  • Platform & MLOps — pipelines, serving, deployment, observability, inference cost. You want the system, not the model.
  • Modelling & data science — features, experiments, and whether the number means anything.

Most people lean one way and dip into the others. This opening is centred on the first two. If modelling is where you'd want to spend most of your time, our Senior Data Scientist opening (in Czechia or Slovakia) is the better fit, and applying to both is fine.

What you'll need

  • 5+ years of Python engineering. You build production services, not scripts, and you have opinions about testing them.
  • Real experience running ML in production — serving, retraining, monitoring, and the specific ways ML systems fail that ordinary services don't.
  • Solid software architecture fundamentals: scalable APIs, microservices, data flow design.
  • Cloud platform depth — we run on GCP and Databricks; AWS or Azure background transfers fine. Plus Git and CI/CD as a matter of course.
  • Working English, written and spoken.

Plus real depth in at least one of:

  • Kubernetes, CI/CD and infrastructure-as-code — the platform side.
  • Distributed data processing: Spark on Databricks, Dataproc, or equivalent.
  • Feature stores, model registries, or experiment tracking tooling — MLflow, Unity Catalog, Vertex AI Model Registry.
  • Evaluation and experiment design — you know why a metric moved, and when it didn't move for the reason everyone assumes.

Also good: you use agentic coding tools daily and have a view on where they help and where they quietly don't. We build agents for a living, and people who use them tend to have better instincts about them.

#LI-KP1

The pay range actually offered will take into account a variety of potential factors considered in compensation, including but not limited to skills, qualifications, geographic location, accomplishments, experience, credentials, internal equity and business needs, and may vary from the range listed above.

Base Salary Range1 300 000 Kč—1 600 000 Kč CZK

More things you'll like about Bloomreach:

Culture:

  • A great deal of freedom and trust. At Bloomreach we don’t clock in and out, and we have neither corporate rules nor long approval processes. This freedom goes hand in hand with responsibility. We are interested in results from day one. 
  • We have defined our 5 values and the 10 underlying key behaviors that we strongly believe in. We can only succeed if everyone lives these behaviors day to day. We've embedded them in our processes like recruitment, onboarding, feedback, personal development, performance review and internal communication. 
  • We believe in flexible working hours to accommodate your working style.
  • We work virtual-first with several Bloomreach Hubs available across three continents.
  • We organize company events to experience the global spirit of the company and get excited about what's ahead.
  • We encourage and support our employees to engage in volunteering activities - every Bloomreacher can take 5 paid days off to volunteer*.
  • The Bloomreach Glassdoor page elaborates on our stellar 4.7/5 rating. The Bloomreach Comparably page Culture score is even higher at 4.9/5

Personal Development:

  • We have a People Development Program - participating in personal development workshops on various topics run by experts from inside the company. We are continuously developing & updating competency maps for select functions.
  • Our resident communication coach Ivo Večeřa is available to help navigate work-related communications & decision-making challenges.*
  • Our managers are strongly encouraged to participate in the Leader Development Program to develop in the areas we consider essential for any leader. The program includes regular comprehensive feedback, consultations with a coach and follow-up check-ins.
  • Bloomreachers utilize the $1,500 professional education budget on an annual basis to purchase education products (books, courses, certifications, etc.)*

Well-being:

  • The Employee Assistance Program -- with counselors -- is available for non-work-related challenges.*
  • Subscription to Calm - sleep and meditation app.*
  • We organize ‘DisConnect’ days where Bloomreachers globally enjoy one additional day off each quarter, allowing us to unwind together and focus on activities away from the screen with our loved ones.
  • We facilitate sports, yoga, and meditation opportunities for each other.
  • Extended parental leave up to 26 calendar weeks for Primary Caregivers.*

Compensation:

  • Restricted Stock Units or Stock Options are granted depending on a team member’s role, seniority, and location.*
  • Everyone gets to participate in the company's success through the company performance bonus.*
  • We offer an employee referral bonus of up to $3,000!
  • We reward & celebrate work anniversaries -- Bloomversaries!*

(*Subject to employment type. Interns are exempt from marked benefits, usually for the first 6 months.)

Excited? Join us and transform the future of commerce experiences!

If this position doesn't suit you, but you know someone who might be a great fit, share it - we will be very grateful!

Any unsolicited resumes/candidate profiles submitted through our website or to personal email accounts of employees of Bloomreach are considered property of Bloomreach and are not subject to payment of agency fees.

#LI-Remote

How we rate this

Senior AI/ML Engineer at Bloomreach rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsML OpsVertex AIMLflowDatabricks

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$200k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. What are the limits of Vertex AI that you've run into, and how did you work around them?
  4. What's a project where you used MLflow hands-on?
  5. Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: AI agents, ML Ops, Vertex AI, MLflow, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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