Senior AI/ML Engineer
Pubblicato il 28-10-2026 - Camlin Group in Parma
Senior AI/ML Engineer
Sia tra i primi a candidarsi: legga la panoramica completa del ruolo qui sotto, quindi invii la sua candidatura per essere preso/a in considerazione.
Camlin Group Parma, Other / Non-US, Italy
About this position
About Camlin
Camlin is a global technology leader that operates with the vision of bringing revolutionary products to life for a wide range of industries, including power and rail, and also has interests in a number of R&D; projects in a variety of scientific sectors.
At Camlin we believe in high quality engineering and design, allowing us to develop market leading products and services. In short, we love creating value for our customers by solving difficult problems. As of now, Camlin operates in over 20 countries worldwide.
The Role
Wearelookingfor aSenior AI/ML Engineerto provide technical leadershipacrossAI and datainitiatives. Thisisahands-onindividualcontributorroleforsomeonewhocan takeambiguousAI/MLproblems,understandthe technical challenges,shapepracticalsolutionsand breakthemdownintoexecutableengineering work.
You'llworkcloselywithengineers, data scientists, product, domainexperts, Delivery and Architecture to turnideasintotechnicallysound, production-readysolutions.You'llhelp teams makedifficulttechnicaldecisions,identifyrisks andunknownsearly, and provide the technicaldirectionneededtomovecomplexinitiativesforward. Success inthisrolemeanshelpingteams makebettertechnicaldecisions,reducinguncertaintyearlyandimprovingthequalityandpredictabilityof engineeringexecution.
Thisisahybridpermanentrole, with 3 days on-site and 2 days working from home.
WhatYou'llWork On
You'llhelp build AI and data productsusedin energyenvironments,including:
-
- Predictivemaintenanceforcriticalinfrastructure
- Anomalydetectionon industrialsensordata
- Asset monitoring andoperationalintelligence
- Energy forecasting and time-seriesmodelling
- Production ML systemsoperatingon large-scalemultimodaldatasets
Thesearedifficultreal-worldproblemsinvolvingnoisyand incompletesensordata, sparse labels, large-scale time-seriesdatasets andevolvingoperationalrequirements.
WhatYou'llDo
-
- Shape technical solutions — TurnambiguousAI/MLproblemsintoclear,practicaltechnicalapproaches.
- Break down complex initiatives — Translatehigh-levelproblemsintotechnicalcomponents,dependenciesandexecutableengineering work.
- Guide AI/ML decisions — Make andcommunicatetrade-offsacrossdata, models and systems, balancingquality, reliability, complexity, cost and performance.
- Provide technical leadership — Work withengineers, data scientists, product and domainexpertsto resolvecomplextechnical challenges andmaintaina clear engineeringdirection.
- Improve engineering quality — Establishgood practices and patternsthatmake AI/ML systemsreliable,maintainableandscalable.
WhatWe'reLookingFor
We'relookingforsomeonewhocombines strong AI/ML engineering capability with sound technicaljudgementand apragmaticapproachto solvingcomplexproblems.
Youwilllikelyhave:
-
- Significantexperiencebuildingreal-world AI, ML or data products.
- Strongunderstandingof AI/ML systems, from data andmodellingthroughto production.
- Experiencetakinginitiativesfrom anuncertainorearly-stage ideathroughto a workingsolution.
- Strong software engineeringfundamentals,particularlyin Python.
- Experience working with data-intensive or time-seriessystems.
- Theabilitytoreasonaboutsystem design,dependencies,scalability, reliability andoperationalconstraints.
- Strongjudgementwhenevaluatingtechnical options and trade-offs.
- Theabilitytocommunicatetechnicaldecisionsclearlytobothtechnical and non-technical stakeholders.
- Experience workingeffectivelywithengineers, data scientists, product and domainexperts.
- A collaborativeapproach, with the confidence to challengeassumptionsconstructively.
You don't need to be the deepest specialist in every AI/ML technique. We'relookingforsomeonewhocanconnectthedifferentpieces, make good technicaldecisionsand help teams solvedifficultproblems.
Technology
Ourcurrenttechnologyenvironmentincludes:
-
- Python
- Apache Spark
- Databricks
- MLflow
- Large-scale industrial and time-seriesdatasets
Wedon'texpectyoutohaveusedeverytechnologyin thestack. Strong engineeringfundamentalsand theabilitytolearnandapplytherighttoolsmattermorethanmatchingeveryitem.
Why This Role
Work onreal-worldindustrial and energy datasets.SolvetechnicallychallengingAI/MLproblemswithvisiblebusiness impact.Havemeaningfultechnicalinflue