Senior Machine Learning Engineer
Bloomreach is hiring a Senior Machine Learning Engineer. Level rates it ; you can apply on Bloomreach.
Level's read on this job
- Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Qdrant, Milvus and PyTorch.
- Level classifies it as a senior role.
- Level lists 67 other open roles at Bloomreach.
- The role was posted within the past week.
AI in this role
Senior Machine Learning Engineer to scale search and personalization ML systems and pipelines in production.
- 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.
Bloomreach is seeking a Senior Machine Learning Engineer to join our Search Scaling team. The team takes the ML and AI behind Bloomreach search and makes it run in production: in the live search path that answers every shopper query, and in the data pipelines that prepare product catalogs for search.
Our search powers online stores for many merchants, each with its own catalog, vertical, language and region. The Scaling team's job is to make our search and discovery features work well for all of them, and to turn models into reliable, low-latency, cost-efficient systems at that scale.
We are looking for someone who combines solid ML expertise with strong software engineering skills and takes end-to-end ownership of technical problems. You will partner closely with our Search Quality team, which develops the relevance and ranking models behind our search.
Your Responsibilities
- Design, build and operate ML components in the search serving path, within tight latency budgets.
- Build query-time ML that helps search understand and handle each query.
- Build and scale ML and LLM data pipelines across large product catalogs, with attention to cost and freshness.
- Tune models across merchants, verticals and languages.
- Build and scale online features and model serving infrastructure.
- Set up offline evaluation and safe rollout for production models: baselines, A/B tests, fallbacks, and latency and cost tracking.
- Improve observability and diagnosis of ML systems in production.
- Work with Search Quality engineers to bring their models into production within latency and cost targets.
- Contribute to technical design and influence decisions across teams.
Qualifications
- BE/B.Tech/ME/M.Tech in Computer Science or a related discipline, with a strong mathematical foundation and excellent programming skills in Python. Experience with a backend language such as Go or Java.
- 5+ years of experience building ML-driven systems in production.
- Strong software engineering skills, with hands-on experience serving ML models and LLMs in scalable cloud systems (AWS/GCP) under tight latency and cost budgets.
- Experience building large-scale data and ML pipelines.
- Strong problem-solving and analytical skills: able to break a problem down into its model-training and backend-engineering parts, and, during development, analyze results to pinpoint the cause of an issue and choose the right next step.
- Experience working across multiple customers, domains or languages.
- Working knowledge of search, such as query understanding, ranking, autosuggest or faceting.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
Preferred Qualifications
- Experience with Solr, Elasticsearch or a similar search engine.
- Experience with vector search in production, such as Milvus or Qdrant.
- Experience building evaluation, observability or explainability tooling for ML models, LLMs and serving systems.
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.
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How we rate this
Senior Machine Learning Engineer at Bloomreach rates 90 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.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $197k
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
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where search scaling was part of your work. What did you do?
- Tell me about a project where latency optimization was part of your work. What did you do?
- Tell me about a project where mlops was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Machine learning, Search Scaling, Latency Optimization, and MLOps. 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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