PURPOSE OF THE JOB
To lead development and scaling-up of production-ready AI systems. To combine traditional software engineering (frontend/backend) with python machine learning LLMs and MLOps to build deploy and maintain end-to-end AI-powered applications. This role needs hands-on technical expertise to drive innovation while mentoring high-performing teams.
KEY RESPONSIBILITIES:
Technical:
- Design and architect end-to-end Data science Machine Learning (ML) Deep Learning (DL) and Gen AI Video Analytics solutions. Exposure to Agentic AI will be preferred.
- Lead the development and deployment of AI solutions ML models and Gen AI solutions.
- Hands-on involvement in designing models using AI solutions for code generation using tools such as Google CLI/Claude Desktop reviewing code and troubleshooting issues in AI ML DL Gen AI solutions.
- Drive adoption of Gen AI Agentic AI solutions.
- Establish best practices for ML model development testing deployment and production monitoring. Experience with ML Ops will be preferred.
- Ensure scalable robust and maintainable data engineering pipelines and solutions
- Ensure designed AI solutions integrate seamlessly with existing Cloud Infrastructure enterprise systems and platforms.
Leadership & Stakeholder Management:
- Contribute to data-driven decision making across the unit and drive adoption of AI systems.
- Contribute to deliver excellent presentations to communicate strategy project status and results influencing key decision-makers.
- Provide technical mentorship and guidance to team on AI solutions
- Foster a collaborative innovative team culture focused on continuous learning
Key Skills
- 8-15 years of progressive experience in software development and extending into Data Science AI ML DL Gen AI Agentic AI technologies.
- Minimum 3 years of hands-on experience in Data Science ML DL Gen AI. (LLMs RAG Fine-tuning)
- Experience with cloud services on platforms like (AWS GCP or Azure)
- Strong skills in designing & implementing DS AI ML ML Ops and Gen AI solutions using python R Scala Spark.
- Strong foundation in Database systems data modelling and data architecture (SQL NoSQL vector databases)
- Exposure to SAS VIYA analytics platform will be preferred
- Excellent written verbal communication skills and excellent inter-personal and presentation skills.
- Excellent time management escalation management and prioritization skills.
- Excellent problem-solving and critical thinking skills.
Experience Required
- 8-15 years of experience as Lead S/W Engineer Senior Data Scientist Senior ML Engineer Senior Gen AI Engineer
Educational Qualifications
- Bachelors or Masters degree in Computer Science Engineering or a related field.
- Certifications in areas such as Data Engineering Cloud Skills AI/ML Gen AI Agentic AI will be an added advantage.
Required Skills:
AIMLMachine LearningArtificial IntelligencePythonLLMsDeep LearningGen AIAgentic AIData ScienceMLOpsData ScientistAI EngineerData Engineering
PURPOSE OF THE JOB To lead development and scaling-up of production-ready AI systems. To combine traditional software engineering (frontend/backend) with python machine learning LLMs and MLOps to build deploy and maintain end-to-end AI-powered applications. This role needs hands-on technical experti...
PURPOSE OF THE JOB
To lead development and scaling-up of production-ready AI systems. To combine traditional software engineering (frontend/backend) with python machine learning LLMs and MLOps to build deploy and maintain end-to-end AI-powered applications. This role needs hands-on technical expertise to drive innovation while mentoring high-performing teams.
KEY RESPONSIBILITIES:
Technical:
- Design and architect end-to-end Data science Machine Learning (ML) Deep Learning (DL) and Gen AI Video Analytics solutions. Exposure to Agentic AI will be preferred.
- Lead the development and deployment of AI solutions ML models and Gen AI solutions.
- Hands-on involvement in designing models using AI solutions for code generation using tools such as Google CLI/Claude Desktop reviewing code and troubleshooting issues in AI ML DL Gen AI solutions.
- Drive adoption of Gen AI Agentic AI solutions.
- Establish best practices for ML model development testing deployment and production monitoring. Experience with ML Ops will be preferred.
- Ensure scalable robust and maintainable data engineering pipelines and solutions
- Ensure designed AI solutions integrate seamlessly with existing Cloud Infrastructure enterprise systems and platforms.
Leadership & Stakeholder Management:
- Contribute to data-driven decision making across the unit and drive adoption of AI systems.
- Contribute to deliver excellent presentations to communicate strategy project status and results influencing key decision-makers.
- Provide technical mentorship and guidance to team on AI solutions
- Foster a collaborative innovative team culture focused on continuous learning
Key Skills
- 8-15 years of progressive experience in software development and extending into Data Science AI ML DL Gen AI Agentic AI technologies.
- Minimum 3 years of hands-on experience in Data Science ML DL Gen AI. (LLMs RAG Fine-tuning)
- Experience with cloud services on platforms like (AWS GCP or Azure)
- Strong skills in designing & implementing DS AI ML ML Ops and Gen AI solutions using python R Scala Spark.
- Strong foundation in Database systems data modelling and data architecture (SQL NoSQL vector databases)
- Exposure to SAS VIYA analytics platform will be preferred
- Excellent written verbal communication skills and excellent inter-personal and presentation skills.
- Excellent time management escalation management and prioritization skills.
- Excellent problem-solving and critical thinking skills.
Experience Required
- 8-15 years of experience as Lead S/W Engineer Senior Data Scientist Senior ML Engineer Senior Gen AI Engineer
Educational Qualifications
- Bachelors or Masters degree in Computer Science Engineering or a related field.
- Certifications in areas such as Data Engineering Cloud Skills AI/ML Gen AI Agentic AI will be an added advantage.
Required Skills:
AIMLMachine LearningArtificial IntelligencePythonLLMsDeep LearningGen AIAgentic AIData ScienceMLOpsData ScientistAI EngineerData Engineering
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