Staff Machine Learning Engineer
Bloomreach is hiring a Staff 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.
- The posting mentions PyTorch, TensorFlow and RAG among its tools and skills.
- Level classes it as a lead role.
- Bloomreach has 73 other open roles on Level.
AI in this role
- 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 seasoned Staff Machine Learning Engineer to join our Search Quality team and lead the design and implementation of machine learning and Al-driven solutions that improve search relevance and discovery experiences for our customers. The Search Quality team focuses on building intelligent, scalable solutions that understand user queries, product catalogs, and behavioral signals to deliver the most relevant search results. We work at the intersection of Machine Learning, Information Retrieval, Search Relevance, and Software Engineering to solve challenging problems across the search stack. This is a Staff ML Engineer role, so we are looking for someone who can combine strong ML expertise with solid software engineering skills and take end-to-end ownership of complex technical problems. You will work closely with engineers, architects, and product teams to research, build, evaluate, and productionize ML-driven solutions for search.
Your Responsibilities
● Own the technical roadmap and provide architecture leadership for ML and AI-driven relevance solutions.
● Design, develop, and enhance ML/AI models and algorithms for Search and Relevance.
● Own model evaluation and experimentation frameworks to ensure high-quality deployments.
● Work with search queries, product catalogs, user behavior, and other data to identify patterns and improve search quality.
● Work closely with software and data engineers to integrate and scale ML components into production systems.
● Analyze search and relevance data to identify problems and drive improvements.
● Mentor engineers and influence cross-team decisions to align engineering and product goals.
● Stay up to date with developments in Machine Learning, Information Retrieval, and Generative AI.
Qualifications
● BE/B.Tech/ME/M.Tech in Computer Science or a related discipline, with a strong mathematical foundation and excellent programming skills, primarily Python, alongside proficiency in a backend language such as Java or Go.
● 8+ years of experience building ML-driven systems and algorithms in production.
● Strong software engineering skills, with experience building low-latency, scalable distributed systems in a cloud production environment (AWS/GCP/Azure).
● Strong background in Search, Information Retrieval, Ranking, or Search Relevance, working with large-scale data and ML systems.
● Hands-on experience applying LLMs to Search/ML problems, including quality, latency, and cost trade-offs.
● Experience working across multiple merchants, domains, and languages.
● Strong background in NLP and Search Quality techniques, including intent identification, query understanding, data analysis, and domain-specific ML model tuning.
● Relevant search retrieval experience in at least one area: RAG, lexical search, vector search, or recommendation systems.
● Experience with deep learning frameworks such as PyTorch or TensorFlow.
● Strong problem-solving and analytical skills.
● Effective communication skills in English, both verbal and written.
Preferred Qualifications
● Prior experience building or working with LLM evaluation frameworks.
● Hands-on experience implementing hybrid search architectures.
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
Staff Machine Learning Engineer at Bloomreach rates 97 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
- $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
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, AI Evaluation, NLP, and PyTorch. 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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