Senior AI/ML Engineer
Czechia
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s listing: Full Time (HC)
From the employer’s posting
What you’ll work on
Full postingOwn ML features end to end, including APIs, training and inference pipelines, and serving
Rewrite model training paths to make research models production-grade
Design systems for terabyte-scale, multi-tenant behavioural data and latency limits
Build quality gates: tests, shadow deployments, A/B tests, drift and performance alerts
Support shipped features, including L3 investigations with client-facing colleagues
From the employer’s posting
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.
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.
Support what you ship, including L3 investigations with our client-facing colleagues.
What you’ll bring
All qualificationsCore experience
- 5+ years of Python engineering.
- 1 300 000 Kč—1 600 000 Kč CZK
Qualification wording
5+ years of Python engineering. You build production services, not scripts, and you have opinions about testing them.
1 300 000 Kč—1 600 000 Kč CZK
Tools in this posting
- Python
- AWS
- Azure
- Databricks
- Google Cloud (GCP)
- Kubernetes
- MLflow
- Spark
Source — Tool mentions in context
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.
- 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.
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.
- 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.
Posting record
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- Live
- First seen by us
- Mar 23, 2026 · 208 days ago
- Recorded sightings
- 256
- Last seen by us
- Oct 18, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
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Job description
- 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.
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.
More things you'll like about Bloomreach:
Culture:
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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.
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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.
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We believe in flexible working hours to accommodate your working style.
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We work virtual-first with several Bloomreach Hubs available across three continents.
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We organize company events to experience the global spirit of the company and get excited about what's ahead.
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We encourage and support our employees to engage in volunteering activities - every Bloomreacher can take 5 paid days off to volunteer*.
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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:
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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.
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Our resident communication coach Ivo Večeřa is available to help navigate work-related communications & decision-making challenges.*
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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.
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Bloomreachers utilize the $1,500 professional education budget on an annual basis to purchase education products (books, courses, certifications, etc.)*
Well-being:
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The Employee Assistance Program -- with counselors -- is available for non-work-related challenges.*
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Subscription to Calm - sleep and meditation app.*
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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.
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We facilitate sports, yoga, and meditation opportunities for each other.
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Extended parental leave up to 26 calendar weeks for Primary Caregivers.*
Compensation:
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Restricted Stock Units or Stock Options are granted depending on a team member’s role, seniority, and location.*
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Everyone gets to participate in the company's success through the company performance bonus.*
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We offer an employee referral bonus of up to $3,000!
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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
Source details
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- Pay
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- Location & working pattern
Czechia
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
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