{"id":3364340,"url":"https://alion.io/job/accenture-ai-ml-engineer-68","title":"AI / ML Engineer","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2096,"ghost_share":0.001,"stale_share":0.146,"repost_share":0.006,"time_to_fill_p50_days":5,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":57000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"GitLab CI","optional":true},{"name":"Grafana","optional":true},{"name":"Helm","optional":true},{"name":"Kubernetes","optional":true},{"name":"Prometheus","optional":true},{"name":"Python","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-30T22:05:05Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Project Role : AI / ML EngineerProject 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.\nMust have skills : Machine Learning Operations\nGood to have skills : NA\nMinimum 7.5 year(s) of experience is required\nEducational Qualification : 15 years full time education\nSummary:\nAs an ML DevOps Architect, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve creating production-ready quality pipelines, applying generative AI models, and exploring various advanced technologies such as deep learning, neural networks, chatbots, and image processing. You will collaborate with cross-functional teams to ensure the successful implementation of AI solutions that meet business needs and enhance operational efficiency.\nMust Have : Hands-on experience on CI/CD & Continuous Testing, Experience with PromptOps including logging, testing, monitoring, and prompt versioning. Strong cloud architecture experience with Azure Cloud and its services,Hands-on experience with Kubernetes, Docker, and Helm for container orchestration, Experience with Infrastructure as Code using Terraform (preferred) or ARM templates, Monitoring and logging (Native Azure monitoring tools, Prometheus, Grafana)\nExperience with GitLab CI/CD pipelines for infrastructure and application (frontend/backend) deployment, Experience implementing DevSecOps practices\nRoles & Responsibilities:\n- Expected to be an SME, collaborate and manage the team to perform.\n- Responsible for team decisions.\n- Engage with multiple teams and contribute on key decisions.\n- Provide solutions to problems for their immediate team and across multiple teams.\n- Facilitate knowledge sharing and mentorship within the team to foster professional growth.\n- Evaluate and implement new technologies and methodologies to improve project outcomes.\nProfessional & Technical Skills:\n- Must To Have Skills: Proficiency in Machine Learning Operations.\n- Good To Have Skills: Experience with cloud platforms such as AWS, Azure, or Google Cloud.\n- Strong understanding of model deployment and monitoring techniques.\n- Experience with containerization technologies like Docker and Kubernetes.\n- Familiarity with programming languages such as Python or R for data analysis and model development.\nAdditional Information:\n- The candidate should have minimum 7.5 years of experience in Machine Learning Operations.\n- This position is based at our Pune office.\n- A 15 years full time education is required.15 years full time education\nAbout Accenture\nAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, militaryveteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicablelaw. 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