Senior Machine Learning Engineer

BloomReach Inc.
Greater London
1 month ago
Create job alert

Slovakia / Czechia / Central & East Europe Remote

Bloomreachhelps businesses personalize the customer experience. It leverages the industry's only real-time customer and product data to train advanced AI, which powerspersonalized marketing, product discovery, content management,andconversational shoppingin a single solution. This AI-driven approach empowers over1,400global brands, including Bosch, Puma, and Marks & Spencer, to grow their businesses. With Bloomreach, personalization flows seamlessly across the customer experience. At every point in their journey, customers are connected with the content they want to see and the products they want to buy. Businesses break the limits of ordinary experiences — and drive measurable growth along the way.

Bloomreach is seeking a seasoned Senior Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for search, recommendation and behavioral insights that are used to personalize digital experiences for our customers. The salary starts at €3,800 gross per month, along with restricted stock units and other benefits. We are currently allowing flexibility for our employees to work from anywhere for the respective region (in this case CEE region) on a full-time basis.

Our centralized data science team spanned across multiple geographies, is responsible for the data science modules that power all the products of the company, including Search Relevance, Recommendation, User Personalization, User Segmentations, Content Intelligence and Conversational Commerce. We invent and apply machine learning, data mining, and information retrieval algorithms to understand, identify, and improve web content discovery. We have built industry leading algorithms in search and recommendations for the commerce space that serve the most relevant experiences using Artificial Intelligence with the goal-building AI driven experiences beyond commerce.

Responsibilities:

  • Design, develop, and enhance ML/AI models which mainly power Search and Recommendation.
  • Process historical data, search queries, product catalog, and images to extract hidden relations and features.
  • Conduct research to explore ongoing cutting-edge ML techniques (especially deep learning) and conduct a quick POC.
  • Work closely with Data Engineers and Senior Data Scientists to integrate and scale ML components to a production-level that can handle terabytes of data.
  • Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences.

Qualifications:

  • BS/MS degree in Computer Science or a related discipline with a strong mathematical foundation and excellent programming skills (primarily Python)
  • 5-8 years experience building ML-driven fast and scalable ML/analytical algorithms in a corporate/startup environment.
  • Strong awareness and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials.
  • Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
  • Excellent exploratory data analysis skills with the ability to slice and dice data at scale using SQL in Redshift/BigQuery.
  • Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies.
  • Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers).
  • Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure).
  • Effective communication skill in English, both verbally and in written form.

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.

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.).

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 paid out immediately after the new hire starts.

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!

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.