Andersen is hiring an ML Engineer (Search) for a project developing AI-powered search, personalized recommendations, and production-grade machine learning solutions at scale.

The customer is a global investment management firm providing tailored investment solutions to institutional and private clients. It combines financial expertise with long-term investment strategies to help clients achieve their objectives while adapting to changing market conditions. The organization focuses on innovation, responsible investing, and operational excellence, continuously enhancing its capabilities to deliver sustainable value and support long-term growth.

The project is focused on developing machine learning solutions that power search ranking and personalized recommendations at scale. It includes building production-grade ML and LLM-based models, deploying them to production, and continuously optimizing performance through experimentation and data-driven evaluation.

Responsibilities:

• Designing and building the deep learning systems behind search ranking, session-based recommendations, and multi-objective personalization, learning from rider behavior and serving users across markets.
• Making ranking consume geographic context and own the recommendation and ranking of pickup points.
• Translating business goals into ML objectives with non-functional requirements.
• Leading evaluation end-to-end, from offline metrics to the design of online A/B tests, and prove a change improves engagement before it ships.
• Partnering with backend engineers to take models from prototype to production, including model serving and latency.
• Partnering with the product manager and operations to turn behavior analysis into concrete features and requirements.
• Owning the ML lifecycle in production, serving, monitoring for drift and building the retraining pipelines that hold quality as data shifts.

Must-haves:

• Machine learning engineering experience with at least three of them building and deploying deep learning models in production for 5 years.
• Direct experience with search, NLP, ranking, recommendation, or relevance systems.
• Expert-level proficiency in Python and its core data science libraries and SQL (e.g., PySpark, Pandas, NumPy, Scikit-learn, PyTorch).
• The ability to design an ML system from scratch in at least one area, including data analysis, annotation, and processing through to a model serving in production.
• Experience turning a business goal into an ML problem with the right proxy metrics and non functional requirements, and designing or substantially contributing to the A/B tests and statistical evaluation that prove impact on user behavior.
• Experience using MLOps tools and practices to manage the ML model lifecycle.
• Experience deploying models to production on ML serving infrastructure and optimizing for latency, and awareness of concept drift and how to detect and manage it.
• The ability to influence teammates and partner teams, and to communicate complex results clearly.
• Level of English – from Upper-Intermediate and above.

Nice-to-haves:

• Experience fine tuning and deploying large language models (or small language models), for query understanding or relevance.
• Subject matter depth in geocoding or autocomplete relevance specifically.
• Experience in mapping, location, or geospatial products.
• Experience building for developing markets, where the underlying map and address data is weak.
• Experience with BigQuery or Databricks certifications.
• Subject matter depth in search, geocoding, ranking, or recommendation systems.
• Experience in mapping, location, or geospatial products.

Reasons why this job would be interesting to you:

• Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc..
• The opportunity to change the project and/or develop expertise in an interesting business domain.
• Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
• Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
• The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
• Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
• Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
• Certification compensation (AWS, PMP, etc).
• Referral program.
• Private health insurance and compensation for sports activities.

Join us!