1+ months

Federal - Senior Machine Learning Engineer

Washington, DC 20044
Organization: Accenture Federal Services

Location: Arlington, VA - Washington, DC

Accenture Federal
Services, a wholly owned subsidiary of Accenture LLP, is a U.S. company with
offices in Arlington, Virginia. Accenture's federal business has served every
cabinet-level department and 30 of the largest federal organizations. Accenture
Federal Services transforms bold ideas into breakthrough outcomes for clients
at defense, intelligence, public safety, civilian and military health

We believe that great outcomes are everything. Its what drives us to turn bold
ideas into breakthrough solutions. By combining digital technologies with what
works across the worlds leading businesses, we use agile approaches to help
clients solve their toughest problems fastthe first time. So, you can deliver
what matters most.

Count on us to help you embrace new ways of working, building for change and
put customers at the core. A wholly owned subsidiary of Accenture, we bring
over 30 years of experience serving the federal government, including every
cabinet-level department. Our 7,200 dedicated colleagues and change makers work
with our clients at the heart of the nations priorities in defense, intel,
public safety, health and civilian to help you make a difference for the people
you employ, serve and protect.

The Machine Learning
Engineer develops machine learning solutions to meet business use cases and to
support experimentation and innovation to advance mission outcomes. The
engineer collaborates with business SMEs, architects, data engineers,
developers and data scientists to identify innovative machine learning
solutions that leverage data to meet business goals. The machine learning
engineer ensures infrastructure and data pipelines are structured to deploy
machine learning solutions.

Key Responsibilities:

+ Understands and translates business and functional
needs into machine learning problem statements

+ Translates complex machine learning problem statements
into specific deliverables and requirements

+ Designs and develops scalable solutions that leverage
machine learning and deep learning models to meet enterprise

+ Works closely with data scientists and data engineers
to develop machine learning algorithms

+ Works on Optimization of Neural Net and Deep Learning
models for inference

+ Translates machine learning algorithms into
production-level code

+ Collaborates with development teams to test and deploy
machine learning models

+ Creates metrics to continuously evaluate the
performance of machine learning solutions

+ Maintains and improves the performance of existing
machine learning solutions

+ Ensures adherence to performance standards and
compliance to data security requirements

+ Keeps abreast with new tools, algorithms and techniques
in machine learning and works to implement them in the organization


+ Proficiency in machine learning algorithms such as
multi-class classifications, decision trees, support vector machines and
deep learning

+ Strong understanding of probability and statistical
models (generative and descriptive models)

+ Ability to run experiments scientifically and analyze

+ Ability to effectively communicate technical concepts
and results to technical and business audiences in a comprehensive

+ Ability to collaborate effectively across multiple
teams and stakeholders, including analytics teams, development teams,
product management and operations

+ Strong Computer Science fundamentals in algorithms,
data structures, OOPS, functional programming


+ 3 years of experience in
building and evolving complex software systems for data processing and
machine learning workloads

+ 3 years of experience with
Big Data processing and ML cloud native services on one or more Cloud Platforms
(GCP, Azure and/or AWS)

+ 3 years of experience with
productionizing developed Machine Learning solutions

+ 3 years of knowledge and
experience with Databases SQL, NOSQL

+ 3 years of experience with

+ 3 years of experience in
interpreting machine learning performance metrics and how to evaluate
usefulness of output

Preferred Skills and

+ Strong grasp of principles and
approaches used in Data-driven systems, processes and algorithms

+ Experience with ML algorithms
for time series data-sets

+ Experience with stream
processing frameworks / Complex event processing engines

+ Scripting skills in at least
one of the following: Shell, Perl, Bash, or Ruby

+ Experience with Performance
Engineering including testing, tuning and monitoring tools

+ Basic familiarity with
continuous integration tools and frameworks

+ Masters Degree

+ Bachelor's degree in data
science, applied mathematics, computer science or otherwise research-based

An active security
clearance or the ability to obtain one may be required for this role.

Candidates who are currently employed by a client of Accenture or an affiliated
Accenture business may not be eligible for consideration.

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).

Accenture is a Federal Contractor and 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.


Posted: 2019-09-30 Expires: 2019-11-29

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Federal - Senior Machine Learning Engineer

Washington, DC 20044

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