Applied AI Engineering, Lead

Deel; Pescara; Remote; EUR 70,000 - 90,000; Full time

Benefits offered by this job

Stock grant opportunities

Flexible working office membership

Competitive total rewards

Role- and location-based perks

Job summary

Deel seeks a leader for its data science team to drive impactful ML models and data-driven insights. You will collaborate with product and engineering teams to deploy analytics, mentor junior scientists, and shape the data science roadmap.

This is a unique chance to influence AI-powered decision-making at scale in a fast-paced global environment with benefits like stock grant opportunities and flexible work options.

Qualifications

• 5+ years of experience in data science, with a strong background in machine learning, statistics, and data modeling.
• Strong expertise in LLM engineering and optimizing cost and latency in production.
• Proficient in programming languages such as Python, R, and SQL.
• Experience leading or managing a data science team.

Responsibilities

• Lead and manage a team of data scientists to deliver high-impact data models.
• Develop and execute data science projects aligned with business objectives.
• Mentor and coach junior data scientists, fostering growth within the team.

Skills

Strong communication

Leadership and mentoring

Ability to manage multiple projects

LLM engineering

Cost and latency optimization

AI-assisted development tools

Tools

Python

R

SQL

TensorFlow

PyTorch

Scikit-learn

AWS

GCP

Azure

Spark

Job description

Overview

In this role you will lead a high-performing data science team to deliver impactful ML models and data-driven insights that support Deel’s growth. You will partner with engineering and product teams to deploy analytics in production and mentor junior scientists. You’ll shape the data science roadmap, stay ahead of industry trends, and ensure reproducibility and reliability of models. This is a chance to drive AI-powered decision making at scale in a fast-moving, global company.

Retribuzione / Benefits

• Stock grant opportunities
• Optional flexible working office membership
• Competitive total rewards
• Role- and location-based perks

Responsabilità

• Lead and manage a team of data scientists to deliver high-impact data models, algorithms, and insights for various business units
• Develop and execute data science projects, ensuring alignment with business objectives and timely delivery
• Guide the team in applying machine learning techniques to solve complex business problems and improve decision-making
• Collaborate with engineering and product teams to ensure seamless deployment of data models and analytics into production
• Mentor and coach junior data scientists, fostering growth and development within the team
• Develop and maintain best practices for data science workflows, ensuring high standards of reproducibility and reliability
• Drive innovation by staying updated on industry trends and emerging technologies in data science
• Ensure the integrity, accuracy, and scalability of data models and analyses
• Communicate data insights and model outcomes to non-technical stakeholders, including leadership teams
• Oversee the continuous improvement of data processes, methodologies, and tools within the team

Requisiti fondamentali

• 5+ years of experience in data science, with a strong background in machine learning, statistics, and data modeling
• Strong expertise in LLM engineering: RAG, agents and tool use, fine-tuning, evals, and optimising cost and latency in production (routing, serving)
• Fluent with AI-assisted development tools (e.g. Claude Code, Cursor) and able to build team practices that let them ship faster without lowering quality
• 2+ years of experience leading or managing a data science team
• Proficiency in programming languages such as Python, R, and SQL
• Strong experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience with cloud platforms (AWS, GCP, Azure) and distributed computing (Spark)
• Solid understanding of statistical analysis and hypothesis testing methods
• Strong communication skills, with the ability to present complex data findings to non-technical stakeholders
• Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment
• Strong problem-solving abilities and a passion for driving data-driven decision-making across the organization

• strong communication
• leadership and mentoring
• ability to manage multiple projects
• LLM engineering: RAG, agents and tool use, fine-tuning, evals
• cost and latency optimization in production
• AI-assisted development tools (Claude Code, Cursor)