Tata Technologies | Project Manager
1 day ago
Chassis Analysis And Simulation
Position / Title-L3.1 -Project Manager
Qualification-BE/M-tech (CS/DataScience/Mech/Electronics)
Post Graduation preferred
Experience-12 to 16 years
Minimum Yrs of Experience: -- 12
Software Competency Requirement
Candidate has to manage team of 8 to 11 data scientists working in AI-ML projects and will be responsible for drafting updates to machine learning models and fine-tuning them to achieve the required prediction accuracy. Below is the skill set required
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 Studio
Secondary Skills: MS-Excel, MS-PowerPoint
Must have : -
Data analysis skills for pre & post processing activities
Ability to evaluate and compare different ML models and algorithms. Technical knowledge on methodology for ML projects
Machine Learning algorithm development & debugging skills
Knowledge of ML model compilation & integration with electronic architecture
CAE software know-how for digital PoC
Experience with vehicle testing activities and optimized test plan preparation
Knowledge on embedded system: Specifying appropriate hardware required for developed model
Knowledge on validation and testing methodology of embedded systems
Preferred to have:
Supervising the data acquisition process
Defining validation strategies
Work closely with other department engineer to create and deploy new product features
Outstanding analytical and problem-solving skills
Ability to work in a team
Should have individual capacity to interact with other team member
Actively participate in new technology development program
Technology/R&D Project Compentency Requirement
TML 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 Conceptualization
1. Idea generation
2. Literature review and benchmarking
3. Concept evaluation theoretically
4. Logic Building
b) Digital PoC
1. Data analysis and pre-processing (virtual data or past measurement data)
2. Concept ML model designing & exploration
3. Digital integration of technology with vehicle
4. Comparative analysis
c) Physical testing
1. Test plan preparation
2. Testing coordination with test agency/joint testing
3. Test data processing
d) ML model finalization
1. Physical data pre-processing, analysis & engineering
2. Draft ML model update and tuning for necessary prediction accuracy
3. Coordination with DPDS for ML model finalization
e) Technology validation and demonstration
1. Proto technology/vehicle preparation and issues resolution
2. Coordination with test agency and supplier for joint validation
3. Project progress review preparation
4. Project gateway & budget tracking
5. Technology demonstration
Design, Development & Deployment Competency Requirement
The 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 & development
1. Specification of electrical/electronic architecture
2. RFI/RFQ preparation and supplier selection activities
3. Coordination with external agency within TML and supplier
4. Specifying appropriate hardware required for developed model
5. Integration of ML applications within the vehicle controller
6. Knowledge on validation and testing methodology of embedded systems
b) Deployment
1. 10-12 years experience building production-quality software
2. Strong experience in System Integration with Application
c. Basic Knowledge of MLOps and docker
d. Implementing MLOps on an Edge Device
e. 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 solutions
k. Foundational Knowledge of Cloud Computing either one AWS, Azure or GCP
Managerial Competency
1. Able to Manage Team of 8-11 Data Scientist
2. Technology validation, deployment and demonstration on vehicle platforms
3. Cross Functional Team Management with internal teams as well as external suppliers
4. Project management related activities
5. Outstanding analytical and problem-solving skills
6. Project documentation and reviews
7. Take lead in improving the design and model accuracy
8. Work on patents / copyrights for the company
9. Ability to collaborate effectively with highly technical resources in a fast-paced environment
10. Hunger and passion for learning new skills
11. 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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