Who We Are  

Core Scientific is a leading provider of infrastructure for high-performance compute in North America. Our mission is to accelerate digital innovation by scaling high-value compute rapidly, efficiently, and responsibly.  We transform energy into high-value compute with unmatched efficiency at scale. The company is a $5 billion publicly traded company (NASDAQ: CORZ). 

We power AI, HPC, and other next-generation data center workloads demanding exceptional computing power, in addition to our digital asset mining operations.  We own and operate nine data centers in seven states, housing advanced infrastructure for our customers. 

What sets us apart? We have an entrepreneurial culture, a "can-do" and collaborative attitude, and we own and control our infrastructure. These strategic advantages enable us to maintain operational excellence, increase efficiency, and rapidly deploy cutting-edge innovations developed by our team of experts. 

Join us and accelerate your career alongside our groundbreaking journey. We seek smart, creative, and collaborative professionals who thrive in a fast-paced, result-driven environment. Ready to be part of something exceptional? Apply today and make an impact at Core Scientific. 

Title 
Data Center Design Engineer

Reports To 
Vice President, Data Center Design  

The Job  

We are seeking a highly experienced and innovative Data Center Design Engineer to lead our data center projects. The ideal candidate will have a deep understanding of data center design, construction, and operations, with a strong background in engineering and project management; roles in operations are a plus but not required. This role involves overseeing the entire lifecycle of data center projects, from initial design through to commissioning and operational handover. 

Responsibilities 

• Lead and manage the design engineering team in the conceptualization, design, and implementation of data center projects, ensuring all systems meet performance, reliability, and safety standards. 
• Provide technical leadership in the design of mechanical, electrical, and plumbing (MEP) systems, ensuring integration with architectural and structural elements. 
• Drive innovation in data center design, incorporating the latest technologies and best practices to enhance efficiency and sustainability. 
• Develop and manage project schedules, budgets, and resources, ensuring projects are completed on time and within budget. 
• Implement and oversee quality control processes to ensure compliance with industry standards, codes, and regulations. 
• Collaborate with clients, architects, contractors, and other stakeholders to ensure project requirements are met and expectations are managed. 
• Identify potential risks and develop mitigation strategies to ensure project success. 
• Maintain comprehensive project documentation, including design specifications, as-built drawings, and operation manuals. 
• Mentor and develop junior engineers, fostering a culture of continuous learning and professional growth within the team. 
• Foster open, respectful, and professional communication directly within the team as well as with co-workers/ teammates and leaders across the organization. 
• Performs other duties as assigned. 

Qualifications 

• A bachelor’s or master’s degree in electrical engineering or a related field is required. 
• 10+ years of experience in engineering, with at least 5 years in a senior or principal role managing data center projects. 
• Professional Engineer (PE) license is preferred. LEED accreditation and other relevant certifications are a plus. 
• Proficiency in AutoCAD, Revit, and other engineering design software. Strong understanding of HVAC, electrical power distribution, and plumbing systems. 
• Proven experience in managing large-scale projects, including budgeting, scheduling, and resource allocation. 
• Excellent verbal and written communication skills, with the ability to present complex technical information to non-technical stakeholders. 
• Strong analytical and problem-solving skills, with a proactive approach to identifying and resolving issues. 
• Demonstrated ability to lead and motivate a team, fostering a collaborative and productive work environment. 

Location 

To be considered for this role, you must reside near the following locations: Miami, FL, Austin, TX, Pecos, TX, Denton, TX, Muskogee, OK, Grand Forks, ND, Calvert City, KY, Marble, NC, Dalton, GA or Auburn, AL 

Travel  

Frequent travel may be required as needed. (50% of the time.) 

Work Environment 

This job operates in a professional office environment and routinely utilizes standard equipment, including laptop computers and smartphones.  

Physical Demands  

While performing the duties of this job, the employee is frequently required to sit, stand, walk, use hands, and lift up to 25 pounds.   

Position Type/ Expected Hours of Work  

This is a full-time position. General hours and days of work are Monday through Friday, 8:00 a.m. to 5:00 p.m. Some nights and weekends may be required.  

Supervisory Experience (Yes or No) 

No 

Who We Are  

Core Scientific is a leading provider of infrastructure for high-performance compute in North America. Our mission is to accelerate digital innovation by scaling high-value compute rapidly, efficiently, and responsibly.  We transform energy into high-value compute with unmatched efficiency at scale. The company is a $5 billion publicly traded company (NASDAQ: CORZ).  

We power AI, HPC, and other next-generation data center workloads demanding exceptional computing power, in addition to our digital asset mining operations.  We own and operate nine data centers in seven states, housing advanced infrastructure for our customers.  

What sets us apart? We have an entrepreneurial culture, a "can-do" and collaborative attitude, and we own and control our infrastructure. These strategic advantages enable us to maintain operational excellence, increase efficiency, and rapidly deploy cutting-edge innovations developed by our team of experts.  

Join us and accelerate your career alongside our groundbreaking journey. We seek smart, creative, and collaborative professionals who thrive in a fast-paced, result-driven environment. Ready to be part of something exceptional? Apply today and make an impact at Core Scientific. 

Title 

Staff Site Reliability Engineer 

Reports To 

Site Reliability Engineering Manager 

The Job 

We are seeking a capable, motivated generalist who thrives in a change-controlled, compliant environment and enjoys working across hybrid cloud and on-premises systems. This role partners closely with application architecture and peer engineering teams while contributing hands-on across platform engineering, DevOps, and SRE. 

This position is expected to take ownership of complex technical initiatives and see them through to completion—balancing hands-on implementation with effective delegation and cross-team coordination. 

Responsibilities 

• Lead end-to-end delivery of complex technical initiatives, from problem definition and design through implementation, rollout, and operation 
• Own the design, implementation, and reliability of systems across hybrid cloud and on-premises environments  
• Take accountability for technical outcomes, including system reliability, scalability, and performance in regulated, change-controlled environments  
• Drive execution by coordinating work across engineers and teams, delegating effectively while remaining hands-on where needed  
• Partner with application architecture and peer teams to shape system design and influence technical decisions  
• Build, deploy, and operate infrastructure and applications using automation and infrastructure as code  
• Implement secure, immutable infrastructure using modern tooling (e.g., Terraform, Kubernetes, Helm, Ansible)  
• Improve observability, monitoring, and incident response practices  
• Establish and promote best practices for reliability, security, and operational excellence across teams  
• Mentor engineers and contribute to raising the technical bar across the organization  
• Foster open, respectful, and professional communication directly within the team as well as with co-workers/ teammates and leaders across the organization  
• Performs other duties as assigned 

Qualifications 

• Bachelor's degree in Computer Science or a related field, 7+ years of experience, or equivalent demonstrated impact in SRE, DevOps, or Infrastructure Engineering 
• Broad technical experience across infrastructure and distributed systems, with the ability to design effective solutions, apply appropriate patterns, and anticipate scaling, reliability, and operational challenges  
• Strong understanding of distributed systems behavior, including application runtime characteristics, service-to-service communication, networking, and failure modes in production environments  
• Experience operating in regulated, compliant, or change-controlled environments  
• Experience working in hybrid environments (AWS preferred; on-premises infrastructure required)  
• Strong experience with Infrastructure as Code, configuration management, and orchestration tools (Terraform, Helm, Kustomize, Ansible)  
• Experience with Kubernetes and virtualization technologies  
• Experience with observability platforms (e.g., Datadog), including building monitoring and alerting integrations  
• Experience with build and release systems (e.g., GitHub Actions, Makefiles, Python tooling)  

Location  

To be considered for the role you must reside near Miami, FL or Austin, TX.  

Travel 

Occasional travel may be required 

Work Environment  

This job typically operates in a professional office environment and routinely utilizes standard equipment, including laptop computers and smartphones. This role may also travel to data center sites, and the work environment at a data center may contain loud noise, construction, and other operational elements. 

Physical Demands  

While performing the duties of this job, the employee is frequently required to sit, stand, walk, use hands, and lift up to 25 pounds.    

Position Type/ Expected Hours of Work  

This is a full-time position. General hours and days of work are Monday through Friday, 8:00 a.m. to 5:00 p.m. The employee is expected to be available generally around U.S. time zones and will be part of an on-call rotation. The current rotation is 1 week every 5 weeks. 

Supervisory Experience (Yes or No)  

No 

Who We Are 

Core Scientific is a leading provider of infrastructure for high-performance compute in North America. Our mission is to accelerate digital innovation by scaling high-value compute rapidly, efficiently, and responsibly.  We transform energy into high-value compute with unmatched efficiency at scale. The company is a $5 billion publicly traded company (NASDAQ: CORZ). 

We power AI, HPC, and other next-generation data center workloads demanding exceptional computing power, in addition to our digital asset mining operations.  We own and operate nine data centers in seven states, housing advanced infrastructure for our customers. 

What sets us apart? We have an entrepreneurial culture, a "can-do" and collaborative attitude, and we own and control our infrastructure. These strategic advantages enable us to maintain operational excellence, increase efficiency, and rapidly deploy cutting-edge innovations developed by our team of experts. 

Join us and accelerate your career alongside our groundbreaking journey. We seek smart, creative, and collaborative professionals who thrive in a fast-paced, result-driven environment. Ready to be part of something exceptional? Apply today and make an impact at Core Scientific. 

Title 

Enterprise Architect 

Reports To 

Chief Technology Officer 

The Job 

As organizations scale, digital systems outpace the assumptions that shaped them. Permissions accumulate, automation compounds, reconciliation logic ages, and integrations drift until policy and documentation alone can no longer ensure that system behavior reflects operational, financial, and revenue-generating reality. 

We are seeking an Enterprise Architect within the Technology organization to ensure that enterprise systems operate with durable precision as complexity increases. The mandate is dual: contain structural risk and harden the enterprise into a disciplined, programmatic system that accelerates revenue, efficiency, and enterprise value. Reporting to the Chief Technology Officer and operating across engineering, data, finance, and operations, this role carries executive sponsorship aligned with CEO directive to strengthen institutional precision so that technology compounds advantage rather than complexity. 

Digital systems define operational truth and revenue execution. When architecture diverges from real-world behavior, inefficiency compounds quietly, throughput slows, reporting distorts, and value erodes. This role engineers durability directly into system design—strengthening control architecture, validating behavior, eliminating operational debt, and maintaining disciplined access models so efficiency becomes structural rather than dependent on vigilance. 

Success is measured by increasing precision at scale. Systems align with operational and financial reality without constant intervention, weaknesses are surfaced before they compound, automation reinforces accountability rather than obscuring it, and improvements in control architecture translate into faster decision velocity, cleaner financial signal, reduced workflow friction, and measurable performance gains. Hardening removes fragility without introducing bureaucracy; precision increases speed. 

This is not a compliance or audit function. It is a high-trust, senior individual contributor role embedded within live enterprise systems with direct access to the CTO and visibility aligned with CEO mandate. 

Responsibilities 

• Investigate enterprise systems to ensure that digital workflows reflect operational, financial, and revenue-generating reality. 

• Map control surfaces across ERP, CRM, data pipelines, automation frameworks, APIs, and integrations, identifying structural weaknesses or inefficiencies.  

• Analyze reconciliation logic embedded within tooling and validate that assumptions remain sound under current scale and transaction velocity. 

• Detect privilege creep, access model drift, override frequency, structural permission risk, and hidden inefficiencies embedded in nuisance technology. 

• Examine automation layers for masked control failures, redundant workflows, and process friction that suppress throughput. 

• Redesign or reinforce enterprise control frameworks where necessary, strengthening architecture without introducing bureaucratic drag. 

• Use structured data analysis, scripting, and AI-accelerated investigative workflows to surface anomalies, quantify exposure, and model performance impact. 

• Translate technical findings into executive-level analysis that connects control integrity to margin protection, decision velocity, and revenue acceleration. 

• Partner with engineering and operations leaders to eliminate structural inefficiencies and convert fragile workflows into hardened programs. 

• Strengthen traceability, documentation, and institutional memory so that system durability scales with growth. 

• Foster open, respectful, and professional communication directly within the team as well as with co-workers/ teammates and leaders across the organization 

• Performs other duties as assigned 

Qualifications 

We are intentionally open to unconventional backgrounds. Exceptional candidates may have experience as: 

• A senior technical leader responsible for building and hardening systems under pressure. 

• A systems engineer or platform architect who has diagnosed and repaired structural fragility. 

• A forensic or investigative professional with strong technical depth. 

• A security or controls engineer with enterprise exposure. 

• A senior operator who has eliminated operational debt while scaling performance. 

You are likely a solution-oriented operator who derives energy from untangling nuisance technology, cleaning up degraded workflows, and eliminating inefficiencies that others tolerate. 

• Think in systems and control surfaces rather than isolated incidents. 

• Understand that structural failure often begins as unmanaged drift. 

• Recognize operational debt embedded in tooling and process before it becomes material loss. 

• Are materially focused and capable of distinguishing signal from noise. 

• Remain calm and precise in ambiguous environments. 

• Are comfortable operating without formal signature authority. 

• Can interrogate systems without destabilizing trust. 

• Thrive on turning fragility into engineered durability. 

• Prefer building hardened programs over writing policies. 

AI proficiency is foundational in this role. You are expected to use AI as a primary analytical engine, a bridging mechanism between systems, and a general-purpose accelerator for investigation, modeling, and solution design. This includes building repeatable AI-assisted workflows that combine data extraction, anomaly detection, hypothesis testing, and structured reporting. 

• Querying structured data using SQL or similar tools. 

• Writing lightweight scripts in languages such as Python to validate assumptions and test system behavior. 

• Navigating APIs, integration layers, automation frameworks, and permission hierarchies. 

• Using AI to synthesize findings, stress-test logic, generate diagnostic artifacts, and accelerate technical validation. 

• Distinguishing between superficial AI usage and disciplined, reproducible AI-driven system interrogation. 

You do not need to be a full-time software engineer. However, you must be technically literate enough to move beyond dashboards and into underlying system logic, and disciplined enough to operationalize AI into repeatable investigative infrastructure. 

Location 

Austin, TX or Miami, FL. While proximity to our core offices is preferred, we prioritize capability and alignment with mandate and will consider remote candidates where appropriate. 

Travel 

Occasional travel will be required up to 25%. 

Work Environment 

This job typically operates in a professional office environment and routinely utilizes standard equipment, including laptop computers and smartphones. This role will also travel to data center sites and the work environment at a data center may contain loud noise, construction and other operational elements,  

Physical Demands 

While performing the duties of this job, the employee is frequently required to sit, stand, walk, use hands, and lift up to 25 pounds.   

Position Type/ Expected Hours of Work 

This is a full-time position. General hours and days of work are Monday through Friday, 8:00 a.m. to 5:00 p.m. Some nights and weekends may be required. 

Supervisory Experience (Yes or No) 

No 

About the Role

As a Technical Deployment Lead on the Claude Agentic Solutions team, you will lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries. You'll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes.

This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion. You will champion our mission in the field, ensure world class delivery, and bring insights back to our product and research teams on a regular basis.

You'll own engagements end-to-end, from SOW through production deployment. You'll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organizational complexity that comes with deploying AI agents in enterprise environments. You need to be technical enough to hold architecture conversations with engineering stakeholders and polished enough to run executive briefings with C-suite sponsors.

Responsibilities

• Own the technical delivery plan for each engagement. Structure SOWs with clear scope, milestones, dependencies, success criteria, and value hypotheses. Translate customer business objectives into a sequenced roadmap that FDEs execute against.
• Lead technical discovery. Map customer workflows, identify constraints, define MVP scope, and shape the solution architecture for custom agent deployments.
• Run day-to-day engineering execution. Drive delivery across Anthropic and customer teams. Keep progress unblocked and sequenced. Make real-time trade-offs on scope and priority to protect the critical path.
• Own product scoping for field engagements. Define the MVP, author requirements documentation, prioritize the engineering backlog, and manage scope against success criteria as requirements evolve.
• Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent Anthropic's technical credibility with senior business and engineering leaders.
• Own value measurement and ROI. Define impact hypotheses, set baselines and KPIs, run pre- and post-deployment measurement, and report outcomes to executive sponsors.
• Codify reusable delivery assets. Build solution patterns, evaluation frameworks, and technical playbooks. Extract what works across engagements and feed field signals back to Product and Research to improve our platform and models.
• Navigate enterprise and regulatory complexity. Security reviews, legal approvals, procurement processes, compliance requirements, and organizational dynamics.
• Manage scope and change. Handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and escalate with clear context when needed.
• Run delivery operations. Sprint ceremonies, milestone reviews, and progress reporting.
• Travel to customer sites. Build relationships, unblock delivery, and accelerate adoption. (25–50% expected).

You May Be a Good Fit If You

• Have led AI/ML engagements/deployments, whether as a founder, data scientist, engineer, researcher, or in a professional services or consulting role.
• Have delivered AI, ML, or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.
• Have experience in a specialized vertical (financial services, life sciences, pharmaceutical, retail, mining, agriculture, etc.).
• Can lead architecture discussions with engineering stakeholders, evaluate technical trade-offs, and pressure-test technical decisions. You won't write production code, but you will own the technical direction of engagements alongside FDEs.
• Have a track record delivering complex, high-stakes technical projects for enterprise clients where outcomes depended on tight coordination and fast decision-making — ideally across multiple workstreams in regulated industries.
• Have executive presence — polished, credible, and comfortable representing Anthropic to senior leaders in high-stakes environments.
• Thrive in ambiguity and bring structure where none exists.
• Have a builder's mindset — you're here to create a function, not join one.

About Avride

Avride is a US-based developer of autonomous vehicles and delivery robots. We develop and operate both autonomous cars and delivery robots that share technologies and mutually benefit from each other's advancements—a unique approach in the industry. 

About the Internship

At Avride, ML Engineer Interns operate at the intersection of cutting-edge academic research and real-world engineering. You will use our massive datasets of real driving logs to train models and develop algorithms.

During this internship, you will be embedded in our Perception team. The Perception team serves as the eyes and ears of our autonomous vehicles, transforming raw data from cameras, LiDAR, and microphones into a precise, real-time 3D understanding of the surrounding world. 

You will be paired with a dedicated senior mentor and work on problems directly impacting real-world driving performance. This program is designed to give you a deep understanding of how to take a theoretical concept or novel system architecture, prototype it, and evaluate its performance within a complex, safety-critical stack.

What You’ll Do

We are currently offering four different internships within our Perception Team for the Summer of 2026. 

Long-Tail 3D Entity Recognition via Pre-Trained 2D Models

• Targeted ML Investigation: Take charge of solving a classic autonomous driving challenge: long-tail entity recognition. You will research how to leverage the broad visual knowledge of pre-trained, open-source 2D models for 3D applications.
• Simulation-Driven Evaluation: Design and run rigorous experiments in our simulation environment to prove your models can detect rare, infrequent objects without sacrificing precision.
• Feature Integration: Work closely with your mentor to prototype and iterate on techniques that adapt these 2D features into our current perception stack.
• Knowledge Sharing: Conclude your internship by sharing your experimental findings, recall/precision trade-offs, and simulation methodology with the research and engineering groups.

RGB-Only 3D Perception & RGB-LiDAR Fusion

• Applied Research Ownership: Lead a scoped research initiative to advance our 3D perception capabilities. You will dive into state-of-the-art literature on RGB-only methods and formulate hypotheses to improve sensor fusion.
• Model Training & Experimentation: Utilize Avride’s extensive real-world LiDAR and camera datasets to train, test, and evaluate ML models using PyTorch, aiming to extract stronger, more reliable signals from RGB data.
• Iterative Prototyping: Partner with your mentor to design and refine algorithms that directly enhance our existing perception baselines.
• Knowledge Sharing: Present your methodology, fusion results, and future recommendations to the broader engineering and research teams at the end of your term.

Data Engineering - Visual Scene Search via Vector Embeddings

• System Architecture & Design: Own the development of a new vector-based search capability to upgrade how we query our scene database. You will research and integrate embedding models (like CLIP) alongside our existing natural language systems.
• Data Tooling Implementation: Build out the backend infrastructure using Python to map and search Avride's massive library of real-world camera data.
• Pipeline Integration: Collaborate with your mentor to deploy these embedding models effectively, unlocking faster and smarter data mining for our labeling and perception teams.
• Knowledge Sharing: Present your system architecture, search performance metrics, and the practical impact of your new tool to the wider engineering organization.

Audio Signal Processing & Siren Recognition Pipeline

• End-to-End Pipeline Creation: Lead an applied engineering project centered on our vehicle microphone arrays. You will design and build a robust data mining pipeline to extract relevant audio signals from raw vehicle logs.
• Auto-Labeling & Fine-Tuning: Leverage large open-source models to automatically label your mined data, then use that dataset to train and fine-tune a compact, efficient onboard ML model for siren recognition.
• Edge Optimization: Partner with your mentor to iterate on the model's performance, ensuring it is highly accurate and lightweight enough for real-time onboard processing.
• Knowledge Sharing: Wrap up your internship by demoing your automated labeling pipeline and the performance of your onboard siren detector to the engineering teams.

What You’ll Need

• Education: Currently pursuing a Bachelor's, Master’s, or PhD (highly preferred) in Computer Science, Robotics, Machine Learning, Applied Mathematics, or a related field with an expected graduation date between Winter 2026 and Spring 2027. 
• Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning, computer vision, optimization, or probabilistic modeling.
• Programming Skills: Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow). Basic familiarity or willingness to learn C++.
• Research Acumen: Ability to read, understand, and implement algorithms from academic research papers. A strong analytical mindset for designing experiments and interpreting data.
• Eagerness to Learn: Highly collaborative, open to feedback, and excited to tackle unsolved problems in the autonomous driving space.

What You’ll Get

• 1:1 Mentorship: Direct guidance from leading researchers and engineers in the autonomous vehicle industry to help you navigate technical roadblocks and grow your career.
• Massive Compute & Data: Access to state-of-the-art driving data to fuel your experiments.
• Networking & Culture: Invitations to tech talks, paper reading groups, intern social events, and cross-team collaborations.

Please note that this is an in-person internship based at our office in Austin, Texas.  We are prioritizing candidates who currently reside within commuting distance of Austin.  We do not provide relocation assistance, travel reimbursement, or housing stipends for this position.

About team

Avride is at the forefront of autonomous mobility, developing and deploying state-of-the-art self-driving cars and delivery robots. We’re shaping the future of transportation and logistics—and our Labeling Team plays a vital role in bringing that vision to life.

The Labeling Backend Team builds the data infrastructure that powers groundbreaking research and development across our labeling pipelines, data preparation workflows, and model training processes. The high-quality labeled data we deliver is critical to advancing our core technologies and supports the diverse range of models that drive our entire business.

About the Role

We are looking for a Research Engineer to improve the quality and representativeness of datasets powering our self-driving systems. You will design algorithms and tools for auto-labeling, data mining and dataset monitoring, combining strong Python engineering with applied ML concepts. Your work will directly enhance data efficiency, reduce labeling costs, and improve model performance.

What You'll Do

• Design and implement algorithms that optimize annotation, including auto-labeling systems that reduce manual effort and increase throughput
• Build data-mining and active-learning pipelines to surface the highest-value samples for training
• Create dataset-quality monitoring systems identifying noise, redundancy, and low-value data
• Develop analytics platforms (databases, dashboards, reporting) to track dataset quality and coverage over time
• Collaborate with ML and Perception teams to integrate research results into production workflows
• Explore emerging approaches (vision-language models, weak supervision, uncertainty estimation) to expand dataset quality and automation

What You’ll Need

• Bachelor’s or Master’s degree in Computer Science or related field
• Strong Python skills for algorithm development and prototyping
• Solid understanding of ML concepts (metrics, evaluation, dataset sampling, etc.)
• Experience with data processing and analysis at scale
• Ability to move between research prototyping and production engineering
• Strong analytical mindset and curiosity to dig deep into data quality problems

Nice to Have

• Experience with auto-labeling, weak supervision, or human-in-the-loop ML
• Exposure to 3D data (point clouds, sensor fusion, 3D annotation pipelines)
• Background in AV, robotics, or large-scale ML dataset development
• Experience with foundation models / VLMs
• Workflow orchestration systems (Argo, Airflow, etc.)
• Backend engineering experience (APIs, ORMs, databases)
• Experience building dashboards or analytics systems (Grafana, Superset, etc.)

Allen Control Systems (ACS) is a cutting-edge defense startup founded by two ex-Navy electrical engineers with a proven track record in robotics and software. We are developing a small, autonomous gun turret that employs advanced computer vision and control systems to precisely target and neutralize small drones and loitering munitions. Our innovative approach requires overcoming significant technical challenges, making this an exciting and dynamic environment for experienced engineers. 

With an engineering-first culture, ACS values technical excellence and continuous learning. Backed by our founders' successful exits from two previous ventures acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop have a real-world impact. 

Position Overview:  

We are seeking a Data Platform Engineer who combines expert-level data infrastructure skills with a strong knowledge of AI & Machine Learning principles. In this role, you will go beyond simple data validation scripts; you will apply your understanding of model training dynamics to design and implement existing and novel approaches to optimize our datasets. 

You will build and maintain large-scale image and video pipelines, but with a focus on data curation strategies—such as coreset selection, embedding-based filtering, and automated complexity scoring. You’ll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but strictly optimized to maximize model performance. 

What You’ll Do: 

• Design and develop a scalable data infastructure, focusing on organization and curation to support continuing increases in data volume and complexity
• Design and implement existing and novel approaches to optimize datasets for model training (e.g., hard example mining, class balancing, de-duplication, embedded-based filtering).
• Support the data infrastructure required for optimal ingestion, transformation, and storing of datasets
• Develop and use synthetic data generation workflows to create realistic synthetic training data for computer vision models.
• Design and own end-to-end image and video pipelines for computer vision model training: multi-source ingestion, QA and visualization, standardization, and organization.
• Coordinate collection of real-world data; coordinate label creation and QA with labelers.
• Develop and use data quality tooling: metrics for balance, drift, and annotation error; active-learning sampling to target gaps; feedback loops from production back to curation. 

• Implement and own dataset versioning, release management, and lineage and metadata cataloging.

What You’ll Need: 

• 3+ years of experience in data engineering or equivalent fields. 
• Solid understanding of data structures and systems design for orchestrating data-related workflows in a rapidly growing environment.
• Proficient in using AWS for data management and processing.
• Proficient in Python for scripting and data processing; proficient with SQL and Linux.
• Educational Background: Bachelor’s or Master’s degree in Computer Science or a related field.
• Proven ability to communicate well across engineering teams, and write and maintain effective documentation. 

You’ll Stand Out: 

• 5+ years of industry experience.
• Experience in image/video data engineering for computer vision projects.
• Experience with PyTorch DeepCore.
• Experience with Unreal Engine. 

What We Offer: 

• Competitive salary
• ACS Equity Package
• Health, Dental, Vision Insurance
• Paid Time Off 

Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.