This is a senior position that requires existing and deep hands-on experience. This is an Applied, Data Science Engineering role: you need to be a data scientist first, with all the deep theoretical foundations to be able to design, build, train, and hypertune ML/DL models, and at the same time have all the practical, hands on, engineering know-how to be able to deploy the models in scalable production environment.
DO NOT apply if you are a:
Our interviews include in-person, face-to-face sessions: do not apply if you can't meet in person, or are unable to take interviews without the help of an AI chatbot.
NO RECRUITERS PLEASE.
Cognomotiv’s Market
The complexity of modern vehicles is increasing at breakneck speed. The introduction of an array of brand-new features, along with refinements on old capabilities, has wildly expanded the role of AI, software, and in-vehicle services in today’s vehicles. More and more functionality is shifting from electronic and mechanical systems to onboard computers controlled by AI. This trend is only accelerating: myriad of new services rely heavily on vehicles being constantly online, while autonomy is becoming increasingly real.
AI and software services offer amazing new opportunities to the automotive world, but bring with them complexity that creates maintenance and repair challenges and operational failures due to underlying hardware, software, and AI that control them.
Who We Are
At Cognomotiv, we help automotive OEMs, Fleet Operators, suppliers, and service centers guarantee the reliability of every vehicle on the road, thanks to state-of-the-art AI that identifies anomalous vehicle behavior in real time, detect and predict issues, and provide guidance on how to fix the problems.
The Cognomotiv solution is a blend of edge and backend AI that performs non-intrusive system diagnosis and prognosis, and makes remediation recommendations with powerful and efficient native models. Our AI is unique in its ability to perform fault and failure detection and prediction in both resource constrained environment as in the edge, as well as in the cloud, and also provide guided repair. Cognomotiv is the ultimate professional grade MRO (Maintenance, Repair, Overhaul) Copilot.
Description
We are seeking an ambitious, self-reliant data science engineer who operates with a sense of urgency and has the ability to thrive in a fast-paced environment. You will design and build the robust, supportable, highly scalable AI foundation of Cognomotiv’s solution:
● Optimize and test ML and statistical models to report and predict systems' health in a variety of subsystems, including mechanical, sensor, and onboard computer.
● Research and develop methods for anomaly detection, failure diagnosis, and root cause analysis using systems data streams as well as information about the system.
● Design and implement models to detect breaches in system reliability.
● Organize and manage fleet data flow, storage, and automated procedures.
● Use variety of ML/DL techniques to mine data for fault patterns and precursors.
● Build and deploy RAG, Generative and Agentic AI to automate scalable guided-repair procedure generation.
● Organize and clearly present or publish findings.
● Assist in porting models to native language for edge computation and learning.
You possess deep technical skills that will be used to drive insights into new products, working closely with both data scientists and engineers. You will have the opportunity to synthesize learning from edge-trained models, a paradigm the entire IoT is striving for. You will have access to new and rich datasets, and use it to directly provide safety and reliability to all fully- or semi-automated systems.
Education & Experience Requirements:
● Degree (advanced preferred, Ph.D., or equivalent experience) in a quantitative field such as statistics or physics
● 5+ years of industry experience in a data science engineering role
● Proficiency in large scale data interaction -- SQL, Hadoop, etc.
● Existing experience in the designing, building, and deploying multimodal ML/DL a huge plus
● Existing experience in working with both streaming and batch mode ML/DL a huge plus
● Expert knowledge of one more more scripting languages (e.g. Python)
● Basic proficiency in at least one object-oriented programming language (e.g. C++, Java)
● Solid understanding and working knowledge of RAG, SLM, Graphs, GNN, Agentic AI
● Solid understanding and working knowledge of fundamental probability and statistics
● Effective communication skills: can turn vague, startup-grade input to concrete, value-added output
● The ideal candidate can independently recognize needs/possibilities and provide creative solutions.
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