Bright Vision Technologies Logo

Bright Vision Technologies

AI Data Infrastructure Engineer

Posted Yesterday
Be an Early Applicant
In-Office
Jackson Heights, NY, USA
100K-150K Annually
Senior level
In-Office
Jackson Heights, NY, USA
100K-150K Annually
Senior level
Design, build, and operate petabyte-scale data pipelines and storage for AI training and evaluation. Implement ingestion, cleaning, deduplication, dataset versioning/lineage, high-throughput loaders, labeling and human-in-the-loop workflows, privacy controls, observability, and cost/performance optimizations while collaborating with ML researchers and maintaining operational documentation.
The summary above was generated by AI
Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled AI Data Infrastructure Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
 AI Data Infrastructure EngineerJob Title: AI Data Infrastructure Engineer
Salary Range: 100k$/Annum-150k$/Annum
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Experience: 6+ years
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are seeking an AI Data Infrastructure Engineer to build and operate the large-scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across diverse modalities. The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency.
Key Responsibilities
  • Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows.
  • Build ingestion systems for diverse modalities including text, image, audio, video, and structured signals.
  • Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale.
  • Develop dataset versioning, lineage, and provenance tracking systems suitable for reproducible training.
  • Build high-throughput data loading systems that maximize GPU utilization during training.
  • Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems.
  • Design storage architectures balancing cost, throughput, and latency across data tiers.
  • Build evaluation dataset construction pipelines with strict integrity and contamination controls.
  • Implement data privacy, redaction, and consent enforcement throughout the pipeline.
  • Collaborate with ML researchers and engineers to align data systems with model development needs.
  • Drive observability of data quality, drift, and pipeline health across the AI data estate.
  • Optimize cost and performance through compression, format selection, and caching strategies.
  • Document data systems, schemas, and operational procedures for broad internal use.
  • Stay current with AI data infrastructure research and emerging open-source tools.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • Six or more years of data engineering experience, with significant work supporting ML or AI workloads.
  • Strong proficiency in Python and at least one JVM or systems language.
  • Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
  • Hands-on experience operating petabyte-scale storage and pipeline systems.
  • Strong understanding of distributed systems, data modeling, and storage formats.
  • Experience with dataset versioning, lineage, and reproducibility for ML workflows.
  • Familiarity with high-throughput data loading for accelerator-based training.
  • Strong software engineering practices including testing, CI/CD, and code review.
  • Excellent communication and cross-functional collaboration skills.
Preferred Qualifications
  • Experience with multimodal datasets at large scale.
  • Familiarity with data quality tooling and dataset evaluation methodology.
  • Exposure to privacy-preserving data systems and regulated data handling.
  • Open-source contributions to data infrastructure projects.
  • Experience supporting frontier model training pipelines.
How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to [email protected] or contact us at (908) 650-6699. Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”
 

Similar Jobs

10 Days Ago
In-Office
New York, NY, USA
175K-215K Annually
Senior level
175K-215K Annually
Senior level
Fintech • Financial Services
Build, operate, and secure the firm's AI infrastructure and developer tooling to enable Python-based AI applications. Implement Azure AI Foundry, integrate LLM APIs (Anthropic, Azure OpenAI), design data pipelines (ADF, Databricks), manage cloud infrastructure (IaC, Kubernetes), and enforce security, governance, and compliance for regulated financial environments.
Top Skills: AksAnthropic Claude ApiAutogenAws BedrockAzure Ai FoundryAzure Ai SearchAzure Api ManagementAzure Data FactoryAzure Data LakeAzure DatabricksAzure DevopsAzure Entra IdAzure Key VaultAzure OpenaiAzure SqlAzure SynapseBicepCosmos DbDatabricks Unity CatalogDockerFastapiFlaskGithub ActionsIamKubernetesLangchainLanggraphMicrosoft FabricPgvectorPowershellPythonS3SastSemantic KernelTerraform
An Hour Ago
Hybrid
New York, NY, USA
123K-223K Annually
Mid level
123K-223K Annually
Mid level
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Field-driven territory sales role responsible for self-sourced, full-cycle selling across Square's product suite. Spend most of the week in-market conducting demos, building pipeline via door-to-door outreach and partnerships, managing Salesforce activity, and consistently exceeding quota while onboarding and growing local merchants.
Top Skills: AfterpaySalesforceSquare
An Hour Ago
Hybrid
New York, NY, USA
122K-149K Annually
Senior level
122K-149K Annually
Senior level
Fintech • Software • Financial Services
Lead and manage onboarding and implementation projects from initiation to launch. Scope solutions, gather requirements, track timelines in Confluence/Airtable, coordinate cross-functional stakeholders, identify and mitigate risks, communicate status to executives, support pre-sales and business development, and apply AI tools to accelerate routine workstreams.
Top Skills: Ai-Assisted ToolsAirtableAPIsAsanaConfluenceJIRAMondaySalesforceSharepoint

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account