Data Scientist GenAI

Reads like a ML Engineer role: putting models into production.

Location not identified

Pay: Pay not listed
Work setting: Remote — work setting source
This is a remote position. We are looking for Data Scientists to join a long-term delivery programme focused on building production-grade AI and Generative AI solutions for enterprise customers. This is a hands-on role centred on real delivery and customer-facing systems, covering classical machine learning, advanced analytics, and LLM-based workflows including RAG. The environment is execution-driven, engineering-focused, and oriented towards measurable business impact
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Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

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What you’ll work on

Full posting

Build, train, evaluate and optimise machine learning models in Python or R
Develop proof-of-concepts and evolve them into production-ready solutions
Implement and improve RAG and LLM-based generative AI pipelines
Prepare, clean and analyse structured and unstructured data
Evaluate model outputs and improve quality, relevance and reliability

From the employer’s posting

Build, train, evaluate, and optimise machine learning models using Python or R

Develop proof-of-concepts and evolve them into production-ready solutions

Implement and improve Generative AI solutions, including RAG and LLM-based pipelines

Prepare, clean, and analyse structured and unstructured data

Evaluate model outputs and continuously improve quality, relevance, and reliability

What you’ll bring

All qualifications

Core experience

Hands-on experience building end-to-end machine learning pipelines
Solid understanding of statistics and core machine learning concepts
Experience with distributed data processing or Spark
Experience working in cloud-based environments
Practical experience with Generative AI, LLMs, and RAG approaches
Experience in fast-paced or delivery-focused project environments

Qualification wording

Hands-on experience building end-to-end machine learning pipelines

Solid understanding of statistics and core machine learning concepts

Experience with distributed data processing or Spark

Experience working in cloud-based environments

Practical experience with Generative AI, LLMs, and RAG approaches

Experience in fast-paced or delivery-focused project environments

Tools in this posting

Python
R
Keras
TensorFlow

Source

- Perform feature engineering and select appropriate modelling techniques - Build, train, evaluate, and optimise machine learning models using Python or R - Develop proof-of-concepts and evolve them into production-ready solutions

- Hands-on experience building end-to-end machine learning pipelines - Very good practical knowledge of Python or R and common data science libraries - Solid understanding of statistics and core machine learning concepts

- Experience with distributed data processing or Spark - Exposure to deep learning frameworks such as TensorFlow or Keras - Experience working in cloud-based environments

Benefits in the posting

Full benefits wording

Comprehensive healthcare
Fully remote model

From the employer’s posting.

Posting record

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Open 4 monthsWe first saw this posting 148 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Jun 3, 2026 · 148 days ago
Recorded sightings: 194
Last seen by us: Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

This is a remote position.

We are looking for Data Scientists to join a long-term delivery programme focused on building production-grade AI and Generative AI solutions for enterprise customers. This is a hands-on role centred on real delivery and customer-facing systems, covering classical machine learning, advanced analytics, and LLM-based workflows including RAG. The environment is execution-driven, engineering-focused, and oriented towards measurable business impact

Responsibilities

Design, develop, and deliver data-driven and AI-based solutions for enterprise use cases
Translate business problems into robust data science and machine learning approaches
Prepare, clean, and analyse structured and unstructured data
Perform feature engineering and select appropriate modelling techniques
Build, train, evaluate, and optimise machine learning models using Python or R
Develop proof-of-concepts and evolve them into production-ready solutions
Implement and improve Generative AI solutions, including RAG and LLM-based pipelines
Evaluate model outputs and continuously improve quality, relevance, and reliability
Contribute to technical design discussions and solution architecture
Collaborate closely with engineers, product teams, and customer stakeholders

Requirements

Strong academic background in Data Science, Mathematics, Statistics, Computer Science, or similar
Hands-on experience building end-to-end machine learning pipelines
Very good practical knowledge of Python or R and common data science libraries
Solid understanding of statistics and core machine learning concepts
Practical experience with Generative AI, LLMs, and RAG approaches
Ability to write clean, production-ready, and maintainable code
Experience working in multidisciplinary delivery teams
Strong communication skills in English

Nice to have
Experience with distributed data processing or Spark
Exposure to deep learning frameworks such as TensorFlow or Keras
Experience working in cloud-based environments
Experience in fast-paced or delivery-focused project environments

Benefits

Solid, competitive salary
Work in multinational environment on international projects
Comprehensive healthcare
Long-term B2B contract with stable project pipeline
Fully remote model

Source details

View original posting ↗

Source notes

Source excerpts

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Pay: No pay amount identified in the saved description.
Location & working pattern: Location not supplied.
This is a remote position. We are looking for Data Scientists to join a long-term delivery programme focused on building production-grade AI and Generative AI solutions for enterprise customers. This is a hands-on role centred on real delivery and customer-facing systems, covering classical machine learning, advanced analytics, and LLM-based workflows including RAG. The environment is execution-driven, engineering-focused, and oriented towards measurable business impact
More source context
- Long-term B2B contract with stable project pipeline - Fully remote model
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

Open source at madiffpl.zohorecruit.com ↗Read the full description ↓

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