Role Description
Role Proficiency:Under guidance from Senior ML Engineers develop ML models that provides accurate results with controls to solve the business problem identified using state of art techniques.
Outcomes
- Executes relevant data wrangling activities related to the problem in order to create dataset
- Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem
- Fine tune the baseline model for optimum performance
- Test Models internally per acceptance criteria from business
- Document relevant Artefacts for communicating with the business
- Work with data scientists to deploy the models.
- Work with product teams in planning and execution of new product releases.
- Set OKRs and success steps for self/ team and provide feedback to goals for team members
- Work with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product
Measures Of Outcomes
- Selection of the appropriate approach to the problem
- Number of successful deployments of the model with optimised accuracy for baseline model
- Adherence to project schedule / timelines
- Personal and team achievement of quarterly/yearly objectives (OKR Assignments HIG Stretch goals)
Outputs Expected
Design to deliver Product Objectives:
- Design ML solutions which are aligned to and achieve product objectives
- Define data requirements for the model building and model monitoring; working with product managers to get necessary data
Updated on state of art techniques in the area of AI / ML :
- Perform necessary research using the latest and state of art techniques to design scalable approaches
- Explain the relevance of the technologies its pros and cons to the product team; enabling accurate design experiences
Skill Examples
- Technically strong with the ability to connect the dots
- Ability to communicate the relevance of technology to the stakeholders in a simple relatable language
- Curiosity to learn more about new business domains and Technology Innovation
- An empathetic listener who can give and receive honest thoughtful feedback
Knowledge Examples
- Expertise in machine learning model building lifecycle
- Clear understanding of various ML techniques with appropriate use to business problems
- A strong background of statistics and Mathematics
- Expertise in one of the domains – Computer Vision Language Understanding or structured data
- Experience in executing collaboratively with engineering design user research teams and business stakeholders
- Experience with data wrangling techniques preprocessing and post processing requirements for ML solutions
- Good knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe
- Familiar with the machine learning model testing approaches
- A genuine eagerness to work and learn from a diverse and talented team
Additional Comments
We are seeking a visionary AI professional to lead the AIOps team within our Intelligent Automation division. The ideal candidate will bring a minimum of 10 years of experience in AI, with deep expertise in ML, Deep Learning, NLP, and Generative AI. The role requires strong technical leadership, R&D focus, and the ability to mentor and lead a team driving cutting-edge AIOps solutions for IT operations management. Responsibilities:
- Lead AIOps Research: Drive research and development of AI solutions for AIOps, focusing on predictive maintenance, anomaly detection, incident correlation, and root cause analysis.
- Project Leadership: Oversee end-to-end delivery of AIOps AI projects, aligning them with organizational goals and client requirements.
- Technical Expertise: Provide expert-level guidance in ML, DL, NLP, and Generative AI technologies to ensure robust and scalable solutions.
- Innovation in AIOps: Explore and implement advanced Generative AI, Large Language Models (LLMs), and agentic AI for intelligent automation and IT operations.
- Team Leadership: Manage, mentor, and inspire a team of AI researchers, data scientists, and ML engineers, fostering a collaborative and innovative environment.
- Collaboration: Partner with cross-functional teams, including product management, engineering, and business stakeholders, to deliver impactful AIOps solutions.
- Strategic Vision: Contribute to the development of AIOps strategies and roadmaps, defining milestones and objectives that drive innovation and business value. Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; advanced degree (Master’s or Ph.D.) preferred.
- At least 10 years of experience in AI, with a focus on ML, DL, NLP, and Generative AI applications.
- Proven expertise in AIOps-specific use cases such as predictive maintenance, anomaly detection, and incident management.
- Proficiency in ML frameworks and libraries like TensorFlow, PyTorch, and Scikit-learn.
- Strong experience with Generative AI and LLMs such as GPT, BERT, or similar transformer models.
- Familiarity with MLOps tools, Databricks, and cloud-based AI services from Azure, AWS, and GCP.
- Demonstrated team leadership experience, with the ability to manage, mentor, and grow technical teams.
- Excellent problem-solving and analytical skills, with a results-oriented mindset.
- Exceptional communication skills to effectively collaborate with diverse stakeholders.
- Ability to operate in a fast-paced, dynamic environment while maintaining a focus on quality and innovation.
Skills
Artificial Intelligence,Machine Learning,Python
