Senior Applied AI Solutions Engineer - Enterprise AI, Italy

Jobgether; Italia; In loco; EUR 174.000 - 304.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive pay

Flexible work

Professional growth

International teams

Impactful projects

Descrizione del lavoro

Jobgether is seeking a Senior Applied AI Solutions Engineer based in Italy to bridge customer needs with our AI platform. You will work across inference, databases, MLOps, and agentic architectures to move workloads from proof-of-concept to production.

You will split time between direct customer engagement and building prototypes, researching new techniques, and shaping product direction through hands-on experimentation and feedback.

Competenze

• Strong hands-on experience with modern machine learning systems, including fine-tuning large models, debugging distributed training workloads, building production RAG or agentic pipelines, and optimizing GPU-based inference.
• Fluency across the modern ML technology stack, including PyTorch, Hugging Face, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent platforms, and vector databases.
• Experience working directly with enterprise ML teams, whether in a solutions engineering, customer engineering, ML engineering, or closely related capacity.
• Demonstrated ability to research emerging techniques, read technical and academic papers, and translate relevant findings into working implementations.
• Strong understanding of ML infrastructure and the ability to troubleshoot complex workloads across the stack.
• Excellent communication skills, with the ability to adapt technical explanations for audiences ranging from ML engineers to senior technology and business leaders.
• Strong customer orientation combined with the ability to maintain technical depth and engineering rigor.
• Ability to work effectively in a highly varied environment, moving between customer problems, technical research, rapid prototyping, and product feedback.
• Experience in Physical AI, robotics, simulation, healthcare and life sciences, drug discovery, medical imaging, clinical NLP, or enterprise AI application development is an advantage.

Mansioni

• Build polished prototypes and technical demonstrations across serverless inference, databases, MLflow, MLOps, and applied AI use cases, including Physical AI and healthcare and life sciences.
• Support enterprise customers hands-on through proof-of-concept design, technical onboarding, validation, and the transition from experimentation to production.
• Act as a technical bridge between customer ML teams and the platform, helping diagnose challenges and accelerate time-to-value during the first months of adoption.
• Research emerging applied AI techniques, including new training approaches, inference optimizations, agentic architectures, and frameworks, and turn relevant discoveries into working prototypes.
• Translate research and customer experience into technical write-ups, recommendations, and actionable product feedback.
• Identify recurring issues across customer deployments and provide specific, evidence-based input that can shape the product roadmap.
• Develop reusable technical assets such as notebooks, reference architectures, benchmarks, and implementation guides to reduce onboarding friction.
• Collaborate with sales, product, engineering, and customer teams to ensure technical insights are converted into practical solutions and product improvements.
• Track developments across the AI ecosystem and help the wider team anticipate important applied AI trends over the next 6–12 months.

Conoscenze

Production ML

PyTorch

Hugging Face

CUDA fundamentals

Kubernetes for ML

MLflow

Vector databases

Enterprise collaboration

Communication

Research skills

Strumenti

Kubeflow

Metaflow

Argo

Ray

Notebooks

Descrizione del lavoro

Jobgether is seeking a Senior Applied AI Solutions Engineer based in Italy to bridge customer needs with our AI platform. You will work across inference, databases, MLOps, and agentic architectures to move workloads from proof-of-concept to production.

You will split time between direct customer engagement and building prototypes, researching new techniques, and shaping product direction through hands-on experimentation and feedback.