ML Ops Engineer
Company: Deloitte
Location: Bethesda
Posted on: May 24, 2023
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Job Description:
Are you a driven problem solver looking to help our clients
tackle some of the most pressing challenges within Government and
Public Services (GPS). Join Deloitte's Program Integrity practice
to help government agencies protect taxpayer money. To address the
threats that perpetuate fraud, waste, and abuse, our clients look
to our team to provide the guidance and solutions required to help
them stay ahead of emerging issues and protect the integrity of
their programs. If you are looking for a rapidly growing,
collaborative environment with opportunities to make an impact and
grow, our Program Integrity team would be a great fit for you!
Work you'll do
Our team detects situations of fraud, waste, and abuse through
reviewing claims. the ML Ops Engineer will be responsible for
learning and implementing new infrastructure.
The team
Deloitte's Government and Public Services (GPS) practice - our
people, ideas, technology and outcomes-is designed for impact.
Serving federal, state, & local government clients as well as
public higher education institutions, our team of over 15,000+
professionals brings fresh perspective to help clients anticipate
disruption, reimagine the possible, and fulfill their mission
promise.
We bring a rigorous approach to help government agencies
effectively detect, prevent, and respond to issues related to
fraud, waste, and abuse. Our team helps tackle these threats by
bringing cutting edge analytics and AI experience with innovative
mindsets. Our Program Integrity team focuses on thought diversity
and collaborative problem solving to help clients address these
challenges holistically, with a common goal to protect the
integrity of their programs.
Qualifications
Required:
Bachelor's Degree in Economics, Finance, Statistics, Mathematics,
Computer Science, Management Information Systems, Engineering,
Business Analytics disciplines, or related area
4-6 Years minimum / no location constraint
2+ years of experience working in a Data Science/Machine Learning
Engineering role.
Proficient in Python, Spark (Pyspark), and SQL
Experience deploying and configuring applications in Kubernetes
Experience automating cloud resource deployment in Terraform.
Comfortable operating in a Linux environment.
Experience developing production applications with Big Data, with
tools like Spark, Hive, and Hadoop.
Experience building model training pipelines in the cloud.
Experience deploying ML services and applications to at least one
major cloud platform (AWS, Azure, GCP, IBM Cloud)
Proficient in software design patterns (e.g. understand
object-oriented vs functional programming principals, inheritance,
writing abstract, reusable, and modular code)
Experience building and deploying microservices as part of Machine
Learning/Data Science applications.
Experience with building continuous integration and delivery
pipelines for Machine Learning applications.
Preferred:
Experience with at least one deep learning framework (e.g.,
TensorFlow, PyTorch, Caffe, MxNET)
Experience developing with AWS managed services such as EMR.
Experience orchestrating the deployment and management of
predictive models in a cloud environment.
Experience working in an AGILE development team.
The wage range for this role takes into account the wide range of
factors that are considered in making compensation decisions
including but not limited to skill sets; experience and training;
licensure and certifications; and other business and organizational
needs. The disclosed range estimate has not been adjusted for the
applicable geographic differential associated with the location at
which the position may be filled. At Deloitte, it is not typical
for an individual to be hired at or near the top of the range for
their role and compensation decisions are dependent on the facts
and circumstances of each case. A reasonable estimate of the
current range is $66,049-$143,556.
You may also be eligible to participate in a discretionary annual
incentive program, subject to the rules governing the program,
whereby an award, if any, depends on various factors, including,
without limitation, individual and organizational performance.
#RLSFY23
Keywords: Deloitte, Bethesda , ML Ops Engineer, Engineering , Bethesda, Maryland
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