Sr. Data Infrastructure Engineer

The Elevator Pitch

Join Evolv as Senior Data Infrastructure Engineer in the Machine Learning & Sensors organization responsible for building and operating the scalable secure and reliable data pipelines that power our AI/ML research and production this role you will own the endtoend data lifecyclefrom collection on thousands to millions of edge devices through cloud ingestion and processing into a centralized data factory enabling model training evaluation and continuous improvement.

Data is the backbone of our mission to deliver bestinclass AIbased weapon detection systems. You will ensure that data flows seamlessly across geographies devices and cloud systems while meeting strict requirements for quality privacy security and scale. This role is ideal for someone who thrives at the intersection of distributed systems cloud pipelines and MLdriven data needs.

Success in the Role: What performance outcomes will you work toward in the first 612 months

In the first 30 days:

• Develop a deep understanding of existing edgetocloud data pipelines and deployment environments.
• Review current data ingestion flows governance policies and cloud infrastructure.
• Assess pain points in data reliability quality and operational scalability.
• Build relationships with AI/ML data science field operations and cloud engineering teams.
• Design and prototype data processing pipelines (both cloud and edge)

Within the first three months:

• Design and implement improvements to core ingestion validation and processing pipelines.
• Deploy scalable data pipeline with AWSbased components (S3 EC2 Lambda Glue Step Functions SageMaker integrations).
• Introduce automated validation workflows to detect corruption missing metadata or malformed data.
• Design and implement automated model evaluation model training and model improvement pipeline to speed up experiments
• Partner with field operations to improve data reliability observability and coverage across deployments.

By the end of the first year:

• Own the entire lifecycle of missioncritical data pipelines supporting AI/ML research and production.
• Architect nextgeneration edgetocloud data systems that scale across millions of devices.
• Define and enforce data governance frameworks including retention access control privacy and lineage.
• Enable ML teams to rapidly experiment through highquality discoverable versioned datasets.

The Work: What type of work will you be doing What assignments requirements or skills will you be performing on a regular basis

EndtoEnd Data Pipeline Ownership:

• Design build and maintain both research and production data pipelines spanning edge devices cloud services and centralized data platforms.
• Own the full data lifecycle: collection ingestion processing obfuscation versioning access retention and retirement.
• EdgetoCloud Data Flow:
• Develop resilient ingestion pipelines capable of handling variable connectivity and device heterogeneity.
• Support secure data transfer from the field to cloud storage systems.
• Collaborate with field ops to enhance data coverage observability and operational robustness.
• Data Quality Governance & Compliance:
• Implement privacypreserving transformations and obfuscation pipelines.
• Build automated cleaning/validation steps to remove duplicates detect corruption and validate metadata.
• Establish data lineage retention policies and access controls ensuring compliance and traceability.

Data Services for AI/ML:

• Provide scalable data services for model training evaluation and research experimentation.
• Support continuous data refresh and retraining workflows.
• Integrate with data labeling services and annotation workflows.
• Enable efficient access patterns for largescale ML workloads.

AWSBased Cloud Infrastructure:

• Build and optimize pipelines using AWS services (S3 EC2 SageMaker Lambda Glue Step Functions).
• Design for costefficiency performance and reliability at scale.

Collaboration & Feedback Loops:

• Partner with AI/ML engineers scientists and data scientists to understand data requirements.
• Translate feedback into automated improvements in data collection labeling and consumption.
• Support crossfunctional teams in exploratory analysis and debugging data issues.

Scaling the Data Factory:

• Design and manage data schema data versioning and data factory updates
• Architect systems that scale globally across millions of devices.
• Ensure the data platform remains flexible for research and reliable for production operations.

Qualifications:

Minimum Qualifications:

• Bachelors or Masters degree in Computer Science Data Engineering Software Engineering or related field.
• 2-3 years of experience building production data pipelines and data platforms that support AI/ML models.
• Strong proficiency in Python C and distributed data processing frameworks.
• Handson experience with AWS services including S3 EC2 SageMaker and Glue.
• Experience designing data systems that support largescale ML training and experimentation.
• Knowledge of data governance access control and lifecycle management.
• Experience collaborating with ML data science operations and cloud teams.

Preferred Qualifications:

• Experience building pipelines spanning edge devices and cloud systems.
• Background working with largescale sensor image or IoT data.
• Familiarity with data labeling tools and annotation workflows.
• Experience implementing dataset versioning lineage and reproducibility systems.
• Understanding of privacy compliance or regulated data environments.
• Experience supporting global multiregion data platforms.

Example Problems You Will Own

• Design a resilient global ingestion pipeline aggregating sensor data from millions of devices.
• Build MLready data services enabling easy discovery versioning and consumption of datasets.
• Implement automated validation and cleaning workflows that dramatically reduce bad data.
• Define and enforce lifecycle and governance policies across research and production datasets.

What is leadership like for this role What is the structure and culture of the team

• You will join our R&D organization reporting directly to VP of ML and this role you will interface with cross-disciplinary teams of highly skilled and autonomous engineers with expertise in Electromagnetics Computer Vision and AI. Our R&D organization includes more than 100 dedicated developers engineers scientists managers and directors each bringing deep technical knowledge and a strong culture of collaboration and support.
• The team culture is one based on building trust collaboration on-going development through kindness authenticity courage drive and fun!

Where is the role located This role is based at our headquarters in Waltham Massachusetts. Due to the nature of our software-enabled hardware products this position requires a minimum of 60% or 3 days per week on-site work.

**Candidates MUST live within commutable distance to our office in Waltham MA**

What is the salary range The base salary range for this full-time position is $129000 - $209000. Our salary ranges are determined by role level and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range individual pay is determined by work location and additional factors including job-related skills experience and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in role posting reflect the base salary only and do not include commission equity or benefits

At Evolv were on a mission to help make public spaces safer through innovative security technology. So were looking for future teammates who embody our values people who:

• Do the right thing always;

• Put people first

• Own it;

• Win together; and continue to

• Be bold stay curious.
  

Our Benefits Include:

• Equity as part of your total compensation package

• Medical dental and vision insurance

• Health Savings Account (HSA)

• A 401(k) plan (and 2% company match)

• Flexible Paid Time Off (PTO)- take the time you need to recharge with manager approval and business needs in mind

• Quarterly stipend for perks and benefits that matter most to you

• Tuition reimbursement to support your ongoing learning and development

• Subscription to Calm

Evolv Technology (Evolv) is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. We welcome and encourage diversity in the workplace and all employment decisions are made without regard to race color religion national social or ethnic origin sex (including pregnancy) age disability HIV Status sexual orientation gender identity and/or expression veteran status or any other status protected by law in the locations where we operate. Evolv will not tolerate discrimination or harassment based on any of these characteristics.

Evolv is committed to offering an inclusive and accessible experience for all job seekers including individuals with disabilities. If you need a reasonable accommodation as part of the job application process please connect with us at .

Evolv participates in E-verify for all employees after the completion of Form I-9.

Required Experience:

Senior IC