Tata Technologies | Project Manager | pimpri-chinchwad
2 weeks ago
Primarily Skills : AIML, C, Python (NumPy, pandas, scikit-learn), pycharm
Preferred Skills : ML OPS,Edge Base Deployment,Statistics, TensorFlow,Keras, Pytorch, Apache Spark, Docker, experience with edge devices (e.g., Raspberry Pi, NVIDIA Jetson) , APIs and Microservices, , MATLAB, System Design, Model Management, Microsoft Visual StudioSecondary Skills: MS-Excel, MS-PowerPoint
Must have : -Data analysis skills for pre & post processing activitiesAbility to evaluate and compare different ML models and algorithms. Technical knowledge on methodology for ML projectsMachine Learning algorithm development & debugging skillsKnowledge of ML model compilation & integration with electronic architectureCAE software know-how for digital PoCExperience with vehicle testing activities and optimized test plan preparationKnowledge on embedded system: Specifying appropriate hardware required for developed modelKnowledge on validation and testing methodology of embedded systems
Preferred to have:Supervising the data acquisition processDefining validation strategiesWork closely with other department engineer to create and deploy new product featuresOutstanding analytical and problem-solving skillsAbility to work in a teamShould have individual capacity to interact with other team memberActively participate in new technology development programTechnology/R&D Project Compentency RequirementTML is working on Chassis System New Technology Development Projects. Projects are based on customer centric feature enhancement of chassis aggregates like steering, brakes, wheels and tires based on Machine Learning (ML). Resource has to execute the project from concept to demonstration taking support from functional teams and external supplier. There will be 8 to 10 R&D projects in a year. Broad area of work consists of following activities:a) Technology Conceptualization1. Idea generation2. Literature review and benchmarking3. Concept evaluation theoretically4. Logic Buildingb) Digital PoC1. Data analysis and pre-processing (virtual data or past measurement data)2. Concept ML model designing & exploration3. Digital integration of technology with vehicle4. Comparative analysisc) Physical testing1. Test plan preparation2. Testing coordination with test agency/joint testing3. Test data processingd) ML model finalization1. Physical data pre-processing, analysis & engineering2. Draft ML model update and tuning for necessary prediction accuracy3. Coordination with DPDS for ML model finalizatione) Technology validation and demonstration1. Proto technology/vehicle preparation and issues resolution2. Coordination with test agency and supplier for joint validation3. Project progress review preparation4. Project gateway & budget tracking5. Technology demonstrationDesign, Development & Deployment Competency RequirementThe development of electrical and electronics architecture is essential for integrating advanced machine learning algorithms that respond dynamically to real-time inputs. After Completion of technology gateway it is required to deploy it on vehicle for validation and demo purpose.
Following are the skillset preffered:a) Electrical/electronics architecture design & development1. Specification of electrical/electronic architecture2. RFI/RFQ preparation and supplier selection activities3. Coordination with external agency within TML and supplier4. Specifying appropriate hardware required for developed model5. Integration of ML applications within the vehicle controller6. Knowledge on validation and testing methodology of embedded systemsb) Deployment1. 10-12 years experience building production-quality software2. Strong experience in System Integration with Applicationc. Basic Knowledge of MLOps and dockerd. Implementing MLOps on an Edge Devicee. Object-oriented languages (e.g. Python, PySpark, Java, C )f. Experience developing CI/CD components for production ready ML pipeline.j. Ability to solve complex challenges/problems and rapidly deliver innovative solutionsk. Foundational Knowledge of Cloud Computing either one AWS, Azure or GCP
Managerial Competency1. Able to Manage Team of 8-11 Data Scientist2. Technology validation, deployment and demonstration on vehicle platforms3. Cross Functional Team Management with internal teams as well as external suppliers4. Project management related activities5. Outstanding analytical and problem-solving skills6. Project documentation and reviews7. Take lead in improving the design and model accuracy8. Work on patents / copyrights for the company9. Ability to collaborate effectively with highly technical resources in a fast-paced environment10. Hunger and passion for learning new skills11. Should attend various meetings as and when required.12. Actively participate in new technology development program, WCQ, audits etc from time to time.
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