• Bachelor's degree in Computer Science, Engineering, Statistics, Technical Science or 3+ years of IT/Software Development/Programming experience
• Minimum 1-2 years’ experience of building and deploying production applications that embed Deep Learning and Machine Learning models, such as Linear Regression, Decision Trees, Random Forest etc.
• Minimum 1-2 years’ experience in designing and deploying production ML models on a variety of cloud infrastructure, e.g. GPUs
• Minimum 1-2 years’ experience setting and using model parameters and hyperparameters i.e. containerize and externalize to tune and scale the model for large datasets. Must have experience of deploying containerized models and ML pipelines using Docker, Kubernetes or equivalent technologies
• Minimum 1-2 years’ experience in engineering models using frameworks such as TensorFlow, Kera’s, Theano, SciKit, PySpark etc.
• Minimum 1-2 years’ experience of building, containerizing and deploying end to end automated ML pipelines using technologies like Spark and Cloud Native services in a large-scale production environment
• Minimum 1-2 years’ experience of using Jupyterhub, Anaconda, Spyder, Databricks, Sagemaker for model engineering, deployments and monitoring.
• Minimum 1-2 years’ experience with performance engineering of these models with very large-scale datasets on a large distributed infrastructure using technologies like Azure Databricks, AWS Sagemaker, AWS EMR etc.
• Minimum 1-2 years’ experience using tools like MLFlow for managing end-to-end machine learning lifecycle for tracking experiments, packaging ML code and deploying models from various ML libraries to model serving and inference platforms
• Experience with different cloud native (e.g. AWS, Azure, Google) as well as third party libraries that support learning models and algorithms.
• Minimum 2+ years of strong programming skills in at least 2 languages from Python, Scala (and Spark), R on AWS, Azure, GCP or on-premise platforms.
• Minimum 1-2 years’ experience working in an Agile environment
• Understanding of advanced math skills (linear algebra, Bayesian statistics, group theory)
• Deep understanding of software engineering and software architecture principles for building and deploying business critical applications.
- Relevant certifications in AI, ML or Data Engineering from AWS, Microsoft or Google
- Understanding of all phases of a complete Data Science Life-cycle
- Strong Experience delivering scaled solutions that generated business outcomes and impacts
- Knowledge and Understanding of Cloud, Hybrid and On-Premise DevOps
Professional Skill Requirements:
Proven success in contributing to a team-oriented environment Proven ability to work creatively and analytically in a problem-solving environment Desire to work in an information systems environment Excellent leadership, communication (written and oral) and interpersonal skills.
All our consulting professionals receive comprehensive training covering business acumen, technical and professional skills development. You'll also have opportunities to hone your functional skills and expertise in an area of specialization. We offer a variety of formal and informal training programs at every level to help you acquire and build specialized skills faster. Learning takes place both on the job and through formal training conducted online, in the classroom, or in collaboration with teammates. The sheer variety of work we do, and the experience it offers, provide an unbeatable platform from which to build a career.
• Proven ability to work creatively and analytically in a problem-solving environment
• Desire to work in an information systems environment
• Excellent communication (written and oral) and interpersonal skills
• Excellent leadership and management skills
• Demonstrated leadership in professional setting; either military or civilian
• Demonstrated teamwork and collaboration in a professional setting; either military or civilian
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States and with Accenture (i.e., H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant status).
Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.
Accenture is an EEO and Affirmative Action Employer of Females/Minorities/Veterans/Individuals with Disabilities.
Equal Employment Opportunity
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.
Accenture is committed to providing veteran employment opportunities to our service men and women.