Senior ML Engineer / Applied ML Engineer | NDA

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

On behalf of the client, GT is looking for a Senior ML Engineer / Applied ML Engineerwho is interested in solving complex matching and search problems at scale, applying ML and algorithms to hundreds of millions of real-world data records.

About the Client

Our client is a leading global management consultancy known for tackling some of the world’s most complex business challenges. With a focus on strategy, transformation, and performance improvement, the firm partners with major organizations across industries to drive lasting impact.

Recognized consistently as a top workplace, it combines deep industry expertise with a collaborative, innovative culture. Its centralized European hub plays a key role in supporting operations across the EMEA region, ensuring excellence and efficiency at scale.

About the Project & Role

We are looking for aSenior ML Engineer / Applied ML Engineer to build and evolve the client’s internalentity resolution system — a core part of the data platform that uses machine learning, LLMs, and search and matching algorithms to turn complex, noisy data into trusted, unified entities.

The system operates at significant scale, processinghundreds of millions of records, and the role will focus on developing and improving the ML models, matching logic, algorithms, and service capabilities behind it.

This is a hands-on engineering role requiring strongPython and SQL, practicalML engineering experience, experience withlarge-scale data pipelines, and strongalgorithmic and problem-solving skills.

This is not a traditional Data Engineering role. The main focus is on building intelligent, production-ready ML systems and solving complex matching and algorithmic problems, with Data Engineering technologies such asSpark/PySparkused to support scalability and productionization.

Responsibilities:

Entity Matching & Distributed Algorithms

• Design and improveentity matching, clustering, and deduplication algorithms at scale

• Implement distributed matching approaches such as:

  • blocking strategies

  • multi-pass matching pipelines

  • nearest-neighbor and similarity-based methods

• Apply and combinerule-based, statistical, and ML-assisted techniques (including embeddings where relevant)

• Optimize candidate generation and scoring to balanceaccuracy, recall, performance, and cost

• Translate algorithmic ideas into scalable implementations usingSpark and SQL transformations

• Continuously experiment with different approaches and iterate based on performance metrics and results

Large-Scale Analytic Engineering

• Design, build, and operate alarge-scale analytic systemprocessing hundreds of millions to billions of records.

• Implement and optimizeApache Spark pipelines for entity matching, deduplication, and clustering.

• Build and maintain complex workflowsusing Airflow and DBT.

• Ensure pipelines arefault-tolerant, observable, and cost-efficient in distributed environments.

SQL & Data Modelling

• Develop and maintainanalytical SQL modelsusingSnowflake or a similar cloud data warehouse.

• Optimize large joins, aggregations, and window functions over very large datasets.

• Design data models that support bothmatching pipelines and downstream consumers.

Data Quality, Validation & Iteration

• Build validation logic and metrics to measurematch rate, precision, recall, and accuracy.

• Support continuous improvements to the matching engine through iterative releases.

• Debug and resolve data quality issues across heterogeneous and imperfect data sources.

Essential knowledge, skills & experience

Core Requirements:

• 5+ years of software development usingPython, ideally in a team lead capacity.

• Solid understanding ofdistributed systems and algorithms (partitioning, shuffles, joins, scalability trade-offs).

• Experience building & working withcomplex data pipelines or data systems

• StrongSQL skills, ideally with Snowflake or similar analytical databases.

• Strong hands-on experience with Apache Spark – Databricks (PySpark or Scala) in production.

• Experience withAI/ML-assisted systems(embeddings, inference, re-ranking).

Matching, Search & Similarity (Required or Willingness to Learn)

• Experience with, or strong interest in,fuzzy and semantic matching techniques, such as:

  • Levenshtein / edit distance

  • Token-based similarity

  • BM25 or other lexical ranking methods

  • Vector embeddings and cosine similarity

  • Approximate nearest-neighbor or vector search concepts

• Strong willingness tolearn and apply advanced semantic matching techniques if not already experienced.
  

Nice-to-Have:

• Experience with data orchestration tools such as Airflow (or equivalents).

• Experience building entity resolution, deduplication, or record linkage systems.

• Familiarity with search or retrieval systems (e.g., Elasticsearch, OpenSearch, vector databases).

• Experience operating data pipelines at very large scale (100M+ records).

• Background in data quality frameworks, validation automation, or QA at scale.

• Experience with Kubernetes or Containerized Functions (e.g., Azure Container Apps, AWS Fargate)

• Experience with Serverless Functions

• Azure or other Cloud Experience

• GitHub Actions

What Success Looks Like

• Matching pipelines scale reliably acrosshundreds of millions to billions of records.

• Measurable improvements inmatching accuracy, recall, and runtime efficiency.

• Faster iteration on matching algorithms without compromising system stability.

• A robust, high-quality entity foundation that enables advanced analytics and downstream applications.

• Understanding of algorithmic and resource constraints to balance system cost and performance

Interview Process

1. Interview with GT Recruiter

2. Cultural Fit Interview

3. Technical Interview

4. Final Interview (optional)

5. Offer

Why join our client?

• Join afast-growing, high-impact team in a top-tier company

• Contribute to an ambitious effort to createthe highest quality, most comprehensive business directory in the world.

• Be part of a dinamic-style group within the company that’s redefining how they deliver consulting throughproductization and data innovation.

• Work with cutting-edge data tools, includingAI/ML enrichment, semantic matching, andmodern cloud-based infrastructure.