Applied Ai Engineering, Lead
Pubblicato il 14-10-2026 - Deel in L'Aquila
h3Overview /h3 pIn 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.
/p h3Retribuzione / Benefits /h3 ul liStock grant opportunities /li liOptional flexible working office membership /li liCompetitive total rewards /li liRole- and location-based perks /li /ul h3Responsabilità /h3 ul liLead and manage a team of data scientists to deliver high-impact data models, algorithms, and insights for various business units /li liDevelop and execute data science projects, ensuring alignment with business objectives and timely delivery /li liGuide the team in applying machine learning techniques to solve complex business problems and improve decision-making /li liCollaborate with engineering and product teams to ensure seamless deployment of data models and analytics into production /li liMentor and coach junior data scientists, fostering growth and development within the team /li liDevelop and maintain best practices for data science workflows, ensuring high standards of reproducibility and reliability /li liDrive innovation by staying updated on industry trends and emerging technologies in data science /li liEnsure the integrity, accuracy, and scalability of data models and analyses /li liCommunicate data insights and model outcomes to non-technical stakeholders,
including leadership teams /li liOversee the continuous improvement of data processes, methodologies, and tools within the team /li /ul h3Requisiti fondamentali /h3 ul li5+ years of experience in data science, with a strong background in machine learning, statistics, and data modeling /li liStrong expertise in LLM engineering: RAG, agents and tool use, fine-tuning, evals, and optimising cost and latency in production (routing, serving) /li liFluent with AI-assisted development tools (e.g. Claude Code, Cursor) and able to build team practices that let them ship faster without lowering quality /li li2+ years of experience leading or managing a data science team /li liProficiency in programming languages such as Python, R, and SQL /li liStrong experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) /li liExperience with cloud platforms (AWS, GCP, Azure) and distributed computing (Spark) /li liSolid understanding of statistical analysis and hypothesis testing methods /li liStrong communication skills, with the ability to present complex data findings to non-technical stakeholders /li liAbility to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment /li liStrong problem-solving abilities and a passion for driving data-driven decision-making across the organization /li /ul ul listrong communication /li lileadership and mentoring /li liability to manage multiple projects /li liLLM engineering: RAG, agents and tool use, fine-tuning, evals /li licost and latency optimization in production /li liAI-assisted development tools (Claude Code, Cursor) /li /ul #J-*****-Ljbffr