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.
Job 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.
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.
Equal Employment Opportunity
Bright Vision Technologies recognizes 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.
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
#J-18808-Ljbffr
