Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : Machine Learning (ML)
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Data Platform Engineer, you will assist with the data platform blueprint and design, collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models. You will play a crucial role in shaping the data platform components.
Roles and Responsibilities:
Design and implement end-to-end machine learning pipelines, from data preprocessing to model training and deployment.
Operationalize ML models using ML flow for tracking, packaging, and deploying models across environments.
Set up and maintain ML Ops practices, including version control, reproducibility, monitoring, and rollback strategies.
Automate workflows for model training, evaluation, validation, and deployment across AWS, Azure, or GCP.
Collaborate with data scientists to productionize experiments and improve model lifecycle processes.
Manage and optimize cloud infrastructure for scalable ML training and inference.
Integrate models into APIs, batch jobs, or real-time inference systems.
Implement governance, lineage, and audit trails for ML artifacts and pipelines.
Technical Skills:
Strong hands-on experience with ML flow, model deployment, and ML lifecycle management.
Proficiency in Python, scikit-learn, TensorFlow, Py Torch, or similar ML libraries.
Experience working with cloud ML services (e.g., SageMaker, Vertex AI, Azure ML).
Understanding of CI/CD and DevOps principles for ML.
Familiarity with Docker, Kubernetes, or serverless architectures.
Experience with feature stores, experiment tracking, and model registries.
Additional Information:
The candidate should have a minimum of 9 years of overall experience
Knowledge of Vector Databases, Lang Chain, or LLM orchestration tools.
Experience with Databricks ML flow integration (if available).
Exposure to monitoring tools for ML drift, data quality, and performance metrics
Knowledge of data privacy and compliance in AI (e.g., anonymization, fairness, explainability
Educational Qualification:
- 15 years full time education is required.
15 years full time education
About Accenture
Accenture 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 at www.accenture.com
Equal Employment Opportunity Statement
We 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, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Skills Required
- Machine Learning (ML) expertise
- Minimum 7.5 years of experience (stated)
- Minimum 9 years of overall experience (additional note)
- 15 years full time education
- Hands-on experience with MLflow (tracking, packaging, deployment)
- Proficiency in Python
- Experience with scikit-learn
- Experience with TensorFlow
- Experience with PyTorch
- Experience with cloud ML services (SageMaker, Vertex AI, Azure ML)
- Understanding of CI/CD and DevOps principles for ML
- Familiarity with Docker
- Familiarity with Kubernetes or serverless architectures
- Experience with feature stores, experiment tracking, and model registries
- Knowledge of Vector Databases and LLM orchestration tools (e.g., LangChain)
- Experience integrating ML models into APIs, batch jobs, or real-time inference systems
- Experience managing and optimizing cloud infrastructure for ML training and inference
- Knowledge of governance, lineage, audit trails, and ML artifact management
- Exposure to monitoring tools for ML drift, data quality, and performance metrics
- Knowledge of data privacy and compliance in AI (anonymization, fairness, explainability)
- Databricks MLflow integration (if available)
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
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Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
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Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
Accenture Insights
What We Do
Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.
