Full Stack Engineer - Washington, United States - Scale AI

Description

Scale AI is seeking a highly skilled and motivated Full Stack Engineer to join our dynamic Federal Engineering team.

As a part of this team, you will play a critical role in delivering high-impact AI-powered mission solutions for government customers.

Our scalable and high-performance platform forms the foundation for these solutions, and your expertise will be instrumental in designing and implementing systems that can handle billions of data points with exceptional performance.

You will:
Design and implement scalable backend systems for Federal customers, leveraging Scale's modern and cloud-native AI infrastructure.

Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.

Develop distributed systems, data-intensive applications, and machine learning infrastructure to enable real impact for mission owners.

Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.

Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.

Contribute to the platform roadmap and product strategy for Scale AI's Federal business, playing a key role in shaping the future direction of our offerings.

Ideally you'll have:
An active TS/SCI security clearance. This is a requirement and candidates will not be considered who do not hold this level of clearance.

Full Stack Development:
Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases.

Cloud-Native Technologies:

Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment.

Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus.

Data Engineering:

Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources.

Understanding of data modeling, data warehousing, and data governance principles.

Machine Learning Infrastructure:
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in designing and implementing machine learning infrastructure. Understanding of model serving, monitoring, and deployment strategies is beneficial.

Problem Solving:
Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.

Collaboration and Communication:
Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment.

Adaptability and Learning Agility:
Willingness to embrace new technologies, learn new skills, and adapt to evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.

The base salary range for this full-time position in our hub location of Washington, DC is $179,200 - $215,040. Compensation packages at Scale include base salary, equity, and benefits.

The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Scale employees are also granted Stock Options that are awarded upon board of director approval.

You'll also receive benefits including, but not limited to:
Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.


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