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Accenture Machine Learning Jobs (NOW HIRING)

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

... of machine learning models into production environments. Responsibilities : • Write clean ... Accenture Federal Services is a leading US federal services company and subsidiary of Accenture.

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Support the implementation, deployment, and scaling of machine learning models in production ... Accenture Federal Services offers a wide variety of benefits. You can find more information on ...

Accenture Federal Services

AI / ML Engineer

Annapolis, MD · On-site

$120K - $221K/yr

Design and train machine learning models using frameworks like TensorFlow and Scikit-Learn for ... Accenture Federal Services offers a wide variety of benefits. You can find more information on ...

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Support the implementation, deployment, and scaling of machine learning models in production ... Accenture Federal Services offers a wide variety of benefits. You can find more information on ...

Accenture Federal Services

AI/ML Engineer

Washington, DC · On-site

$108K - $203K/yr

Hands-on experience with developing machine learning models at scale from inception to business ... Accenture Federal Services offers a wide variety of benefits. You can find more information on ...

Accenture Federal Services

AI/ML Engineer

Washington, DC · On-site

$108K - $203K/yr

Hands-on experience with developing machine learning models at scale from inception to business ... Accenture Federal Services offers a wide variety of benefits. You can find more information on ...

Accenture Federal Services

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

... machine learning models in production environments using tools like Amazon SageMaker, MLflow, or ... Accenture Federal Services is a leading US federal services company and subsidiary of Accenture.

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All JobsAccenture Machine Learning Jobs

Accenture Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do accenture machine learning jobs pay per year?

As of Jun 9, 2026, the average yearly pay for accenture machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Accenture Machine Learning vs Data Scientist?

AspectAccenture Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, Data Science, or related fields; certifications in ML or AIBachelor's or higher in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentConsulting projects, client sites, corporate officesResearch labs, tech companies, corporate offices
Employer & Industry UsageConsulting firms, tech companies, industries adopting AI solutionsTech firms, research institutions, data-driven industries

While both roles involve working with data and machine learning, Accenture Machine Learning professionals typically focus on implementing ML solutions within client projects at a consulting firm, whereas Data Scientists often conduct research, develop models, and analyze data within organizations or research settings. The roles overlap in skills and certifications but differ in work environment and scope.

What does a Machine Learning professional do at Accenture?

A Machine Learning professional at Accenture is responsible for designing, developing, and deploying machine learning models and AI solutions tailored to client needs. They work with large datasets, analyze data patterns, and collaborate with multidisciplinary teams to solve complex business challenges. Their role often involves staying up-to-date with the latest advancements in AI, ensuring the ethical use of data, and driving innovation to deliver actionable insights and automated solutions for clients across various industries.

What are the key skills and qualifications needed to thrive as a Machine Learning professional at Accenture, and why are they important?

To thrive as a Machine Learning professional at Accenture, you need a solid background in statistics, data analysis, and programming (often with Python or R), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms (like AWS, Azure, or Google Cloud), and relevant certifications (e.g., AWS Certified Machine Learning) is highly valued. Strong problem-solving abilities, collaboration, and effective communication help you translate complex data insights into actionable business solutions. These skills are vital for designing impactful AI solutions that meet client needs and drive innovation within multidisciplinary teams.
More about Accenture Machine Learning jobs
What states have the most Accenture Machine Learning jobs? States with the most job openings for Accenture Machine Learning jobs include:
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Accenture Machine Learning jobs near you
Infographic showing various Accenture Machine Learning job openings in the United States as of May 2026, with employment types broken down into 11% Full Time, 61% Part Time, 17% Temporary, and 11% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Data Engineer

Data Engineer

Accenture Federal Services

Suitland, MD • On-site

$123K - $148K/yr

Full-time

Posted 28 days ago

Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

45th of 426 rated business services

Job description

Job Summary:
Accenture Federal Services is dedicated to enhancing the capabilities of the US federal government through technology and innovation. They are seeking a skilled Data Engineer to design, build, and maintain data infrastructure, ensuring efficient data flow and integration of machine learning models into production environments.
Responsibilities:
• Write clean, efficient, and scalable code to build and optimize data solutions using programming languages like Python.
• Design, build, and orchestrate robust and reliable data workflows using tools such as Apache Airflow, dbt, Prefect, or Dagster.
• Work comfortably in cloud environments, with a strong preference for experience in AWS. Experience in GCP or Azure is also highly valued.
• Extract, integrate, and ensure the quality of data from various sources using tools and technologies such as SQL, PostgreSQL, Snowflake, Amazon Redshift, or BigQuery.
• Leverage frameworks like Apache Spark, Databricks, or Apache Kafka to process and manage large-scale data workflows with reliability and efficiency.
• Support the implementation, deployment, and scaling of machine learning models in production environments using tools like Amazon SageMaker, MLflow, or Kubeflow.
• Monitor data pipeline health, troubleshoot issues, and ensure data consistency using tools such as Amazon CloudWatch, Datadog, or Great Expectations.
• Work closely with data scientists, analysts, and other stakeholders to understand data requirements, communicate solutions, and document processes using tools like Git, Jira, and Confluence.
Qualifications:
Required:
• 2 years of experience as a Data Engineer or similar role.
• Strong proficiency in Python or other programming languages relevant to data engineering.
• Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow, dbt, Prefect, Dagster).
• Solid understanding of cloud platforms (AWS strongly preferred; GCP or Azure experience also considered).
• Expertise in SQL and familiarity with relational and columnar databases (e.g., PostgreSQL, Snowflake, BigQuery).
• Knowledge of big data processing frameworks (e.g., Apache Spark, Databricks, or Apache Kafka).
• Familiarity with machine learning workflows and experience implementing MLOps tools (e.g., Amazon SageMaker, MLflow, or Kubeflow) in production environments.
• Strong troubleshooting skills and experience monitoring data pipelines and system health using tools like Amazon CloudWatch, Datadog, or Great Expectations.
• Excellent communication skills and a collaborative mindset, with a focus on documentation and best practices.
• An active TS/SCI federal security clearance is required
Preferred:
• Experience working with large-scale distributed systems.
• Knowledge of data governance and security best practices.
• Proven ability to work in cross-functional teams and contribute to problem-solving and innovation.
Company:
Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the company is headquartered in Arlington, USA, with a team of 10001+ employees. The company is currently Late Stage.

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