AI Developer (NM+)
cummins | 65 days ago | Pune

Competencies:

Action oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.

Balances stakeholders - Anticipating and balancing the needs of multiple stakeholders.

Business insight - Applying knowledge of business and the marketplace to advance the organization’s goals.

Drives results - Consistently achieving results, even under tough circumstances.

Plans and aligns - Planning and prioritizing work to meet commitments aligned with organizational goals.

Tech savvy - Anticipating and adopting innovations in business-building digital and technology applications.

Performance Tuning - Conceptualizes, analyzes and solves application, database and hardware problems using industry standards and tools, version control, and build and test automation to meet business, technical, security, governance and compliance requirements.

Programming - Creates, writes and tests computer code, test scripts, and build scripts using algorithmic analysis and design, industry standards and tools, version control, and build and test automation to meet business, technical, security, governance and compliance requirements.

Solution Configuration - Configures, creates and tests a solution for commercial off-the-shelf (COTS) applications using industry standards and tools, version control, and build and test automation to meet business, technical, security, governance and compliance requirements.

Solution Functional Fit Analysis - Composes and decomposes a system into its component parts using procedures, tools and work aides for the purpose of studying how well the component parts were designed, purchased and configured to interact holistically to meet business, technical, security, governance and compliance requirements.

Solution Validation Testing - Validates a configuration item change or solution using the Function's defined best practices, including the Systems Development Life Cycle (SDLC) standards, tools and metrics, to ensure that it works as designed and meets customer requirements.

Values differences - Recognizing the value that different perspectives and cultures bring to an organization.

Education, Licenses, Certifications:

College, university, or equivalent degree in Computer Science, Information Technology, Business, or related subject, or relevant equivalent experience required. This position may require licensing for compliance with export controls or sanctions regulations.

Experience:

Intermediate level of relevant work experience required. 3-5 years of experience.

QUALIFICATIONS

Key Responsibilities

  • AI Solution Development: Design, build, and deploy AI models including machine learning, natural language processing (NLP), and computer vision tailored to commercial use cases.

  • Cloud Integration: Utilize services such as Amazon SageMaker, AWS Comprehend, Azure Machine Learning, and Azure Cognitive Services to deliver scalable, cloud-native solutions.

  • Data Engineering: Manage large datasets, perform data cleansing, transformation, and feature engineering to support model training and evaluation.

  • Business Application: Implement AI capabilities for use cases like lead scoring, churn prediction, intelligent virtual assistants, and automated support workflows.

  • Cross-Functional Collaboration: Work closely with stakeholders across sales, service, product, and data science teams to align technical solutions with business goals.

  • Innovation & Optimization: Stay current with emerging AI/ML trends and cloud technologies to continuously improve solution performance and relevance.

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

  • Proven experience as an AI Developer, Machine Learning Engineer, or similar role.

  • Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

  • Hands-on experience with AWS (e.g., SageMaker, Lambda, EC2) and Azure (e.g., Azure ML, Functions, VMs).

  • Demonstrated success in applying AI to commercial environments, particularly in sales and service domains.

  • Excellent analytical thinking and the ability to translate business requirements into scalable technical solutions.

  • Strong communication and stakeholder engagement skills.

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