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Careers at Accenture
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AI / ML Engineer

Full Time
full-time
5 Nov 2025
Verified by Turrior

Content + Source + Freshness • 17 Dec 2025 • 95% confidence

80 / 100

Offer value

High value due to extensive experience requirements and strong career advancement opportunities through AI technologies.

  • Work within a reputable firm at the forefront of AI.
  • Lead projects in machine learning and NLP.
  • Engage with cross-functional teams and mentor peers.
  • High experience requirement (12+ years).
Pros
  • Engagement in pioneering AI projects within a reputed company.
  • High demand for expertise in machine learning and NLP.
  • Opportunities to lead and mentor other team members.
Cons
  • Very high experience threshold (12+ years) could limit applicant pool.
  • Potential for a high-pressure environment given project demands.
  • Lack of salary transparency could deter some candidates.

Who it's for

Senior Level • Office-based

Good fit
  • AI specialists with a strong background in ML/NLP.
  • Senior engineers eager to mentor and lead teams.
  • Individuals interested in cutting-edge AI research.
Not recommended for
  • Entry-level applicants lacking relevant experience.
  • Candidates preferring solely independent work.
  • Those uncomfortable in high-demand environments.

Motivation fit

Desire to drive innovation in AI technologies.Interest in mentoring and developing other talent.Aspiration to work on large-scale AI applications.

Key skills

Machine Learning expertise.Natural Language Processing proficiency.Leadership and team collaboration skills.
Score: 80/100 AI verified analysis

About the job

Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Natural Language Processing (NLP)
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions, ensuring that they meet quality standards. You will work with various AI models, including generative AI, deep learning, and neural networks, while also exploring innovative applications such as chatbots and image processing. Collaboration with cross-functional teams will be essential to integrate these solutions effectively into existing systems and pipelines. Roles & Responsibilities: - Expected to be an SME. - Collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Expected to provide solutions to problems that apply across multiple teams. - Facilitate knowledge sharing and mentoring within the team to enhance overall performance. - Continuously evaluate and improve existing processes and systems to optimize efficiency. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning. - Strong understanding of various machine learning algorithms and their applications. - Experience with cloud-based AI services and deployment strategies. - Familiarity with data preprocessing and feature engineering techniques. - Ability to work with frameworks such as TensorFlow or PyTorch. Additional Information: - The candidate should have minimum 12 years of experience in Machine Learning. - This position is based at our Bengaluru office. - A 15 years full time education is required.

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End-to-end AI hiring for modern HR teams

Turrior uses artificial intelligence to create job listings, automate candidate screening, conduct video interviews, and apply comprehensive AI scoring — helping companies hire faster, more accurately, and with lower operational costs.

Key benefits:

  • AI-powered job creation and structured job data
  • Intelligent candidate screening and automated shortlisting
  • Video interviews with AI-based answer analysis
  • Comprehensive AI scoring of skills, experience, and role fit
  • Recruitment process automation and reduced time-to-hire

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