Machine Learning Engineer

Indianapolis, IN, United States

Are you ready to be part of a company that's not just talking about the future, but actively shaping it? Join The AES Corporation (NYSE: AES), a Fortune 500 company that's leading the charge in the global energy revolution. With operations spanning 14 countries , AES is committed to shaping a future through innovation and collaboration. Our dedication to innovation has earned us recognition as one of the Top Ten Best Workplaces for Innovators by Fast Company in 2022. And with our certification as a Great Place to Work , you can be confident that you're joining a company that values its people just as much as its groundbreaking ideas.

AES is proudly ranked #1 globally in renewable energy sales to corporations, and with $12.7B in revenues in 2023 , we have the resources and expertise to make a significant impact as we provide electricity to 25 million customers worldwide. As the world moves towards a net-zero future, AES is committed to meeting the Paris Agreement's goals by 2050. Our innovative solutions, such as 24/7 carbon-free energy for data centers, are setting the pace for rapid, global decarbonization.

If you're ready to be part of a company that's not just adapting to change, but driving it, AES is the place for you. We're not just building a cleaner, more sustainable future - we're powering it. Apply now and energize your career with a true leader in the global energy transformation.

At AES, we have an amazing opportunity to transform the world with renewable energy. As one of the larger provides of renewable energy globally, we are dedicated to using the vast amounts of information available to design Smart Maintenance, Smart Operations, Smart Grid and other Energy related solutions to improve our operations and become the global leader in renewable energy generation.

Machine Learning Engineers are the designers of self-running software that brings machines the ability to automate models that are predictive. They work with data scientists to take information and feed curated data into the models that they've uncovered or discovered. They use theoretical models within the data science sphere and build them out to scale as functioning and productive units or models that handle terabytes of real-time data.

Machine learning Engineers also function as a bridge or intersection for software engineering and data science. They use the available big data tools to improve programming frameworks and to collect raw data from pipelines. They redefine raw data into data science models that are ready to scale. Some machine learning engineers design the software programs that control technological tools, including computers or robots. They can develop algorithms that allow machines to identify trends or patterns in their programming data and as a self-contained unit, and a machine can then guide itself to understand commands, or even to think for itself. Machine learning engineers need a minimum of a bachelor's degree in computer science or related fields.

Primary Duties and Responsibilities

Communicate and reinforce the team's vision, purpose, and strategy.

Collaborate with engineering leaders to transform research into AI capabilities within the platform.

Develop text, image, and video analysis solutions for agents to enhance their business.

Serve as a tech lead on a team of applied and data scientists.

Drive ML projects from conception to completion, collaborating with data scientists, engineers, product teams, and other key partners.

Design, develop, validate, deploy, and handle new functionalities, such as cash flow forecasting solutions.

Partner with QA teams on test automation for new and existing functionalities.

Conduct system integration and tests with other engineers.

Monitor and troubleshoot performance issues in enterprise data pipelines.

Work cross-functionally to identify business problems, design technical solutions, and deliver business impact.

Ensure products are production-ready and function smoothly upon deployment.

Launch new products and features, test their performance, and iterate quickly.

Engage in cutting-edge research and development projects with a small team.

Mentor and guide engineering teams to enhance technical expertise.

Define database structures, identify data types for collection, and set up data analysis software.

Research, modify, and apply data science and data analytics prototypes.

Develop and construct methods and plans for machine learning.

Use test findings for statistical analysis and model improvement.

Source training datasets from the internet.

Train and retrain ML systems and models as vital.

Enhance and expand existing ML frameworks and libraries.

Create machine learning applications tailored to client or customer needs.

Investigate, test, and implement suitable ML tools and algorithms.

Evaluate ML algorithms for their application potential and rank them by success likelihood.

Explore and visualize data to better understand it and identify distribution discrepancies that might affect model effectiveness.

Qualifications

Bachelor's or Graduate's Degree in Computer Science, Math, Statistics or a related discipline.

Advanced math skills (linear algebra, Bayesian statistics, group theory)

Proficiency in applicable software, systems, and processes, such as SIRI, APIs, JAVA, and C.

Extensive data modeling and data architecture skills.

Experience with algorithm design and natural language processing.

Comfortable working with big data, statistics, and frameworks.

Seize the opportunity and adopt new strategies and methods to make a career in a field that cultivates innovation and growth.

Prioritize skills over experience, a clear and deliberate plan can assist aspirants in developing a successful career.

Setting new standards by creating a resume that highlights their skills and qualifications, attracting the right job opportunities, or participating in learning programmes that promote career growth by focusing on skill-building, etc.

Knowledge of Hadoop or another distributed computing systems

Experience working in an Agile environment.

Strong written and verbal communications

At AES, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists. You will also be surrounded by colleagues who are committed to helping each other grow through our outstanding Check-In approach where feedback flows freely.

AES is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, religion, age, sexual orientation, gender identity, disability or veteran status.

AES is an Equal Opportunity Employer who is committed to building strength and delivering long-term sustainability through diversity and inclusion. Respecting all backgrounds, differences and perspectives enables us to improve the lives of our people, customers, suppliers, contractors, and the communities in which we live and work. All qualified applicants will receive consideration for employment without regard to sex, sexual orientation, gender, gender identity and/or expression, race, national origin, ethnicity, age, religion, marital status, physical or mental disability, pregnancy, childbirth, or related medical condition, military or veteran status, or any other characteristic protected under applicable law. E-Verify Notice: AES will provide the Social Security Administration (SSA) and if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.