Bioinformatics Engineer | Remote | US

Mind Moves; Northern (KY); Hybrid; USD 138,000 - 179,000; Full time

Job summary

Mind Moves is seeking a contractor to design and build synthetic data generation pipelines for high-fidelity datasets used in testing AI systems handling sensitive data. You will prototype data solutions and apply privacy-preserving techniques in collaboration with NIH stakeholders.

The role offers remote work in the US, with EST time zone preference, and compensation ranging from $100 to $130 per hour. Contract duration is Sept–Dec, at 20–25 hours per week.

Qualifications

• Experience building synthetic data pipelines with statistical modeling or generative models (GANs/VAEs).
• Experience engineering large-scale genomic/clinical data formats and data transformations.
• Proficiency in Python and SQL with privacy/data science libraries.
• Data engineering/ETL and schema modeling experience.
• Familiarity with AI governance frameworks and federal compliance preferred.
• Eligible for US 1099 contracting; eligible for a federal public trust credential.

Responsibilities

• Design and build synthetic data generation pipelines that replicate data structures and statistics.
• Generate realistic synthetic test/dev datasets for prototyping and red-team testing.
• Apply privacy-preserving techniques, including differential privacy noise injection.
• Validate data fidelity and ensure parity with real data benchmarks.
• Document methods and assess residual privacy risks for releases.
• Collaborate with Red‑Team/Adversarial Security Lead and Biomedical Privacy Engineer.
• Produce methodology docs and data provenance records for DAC review.
• Coordinate with cross‑functional teams across federal agencies and partners.

Skills

Synthetic data pipelines

Statistical modeling

Generative models

Agent-based simulation

Python

SQL

PyTorch

Hail

Polars

Spark

Diffprivlib

Opacus

Tools

Hail

Polars

Spark

PyTorch

Job description

About Mind Moves

Mind Moves is a women-owned Washington, D.C.-based firm helping businesses and governments to embrace, build and deploy ‘human in the loop’ AI solutions to elevate mission and value. We are pioneers with deep expertise in the field of machine learning and AI (both predictive and generative). We have delivered responsibly developed products and services that impact millions of users worldwide, while generating millions of dollars in revenue. We have worked with Fortune 500 corporations and large government entities in health care, supply chain management, financial services and life sciences. We apply a structured methodology and holistic approach to AI transformation and a broad spectrum of technical services centered in the harnessing of people, science and technology.

What you’ll be doing

Designing and building synthetic data generation pipelines that produce high-fidelity, statistically representative datasets modeled on sensitive, controlled-access data sources — without exposing real participant-level information. Your synthetic datasets will let cross-functional teams prototype, test, and red-team AI/agentic systems against realistic data conditions before those systems ever touch production, controlled-access repositories.

Working with Mind Moves

You’ll collaborate with the Principal Investigator/Technical Lead, Biomedical Privacy & Gateway Engineer, Red-Team/Adversarial Security Lead, Cybersecurity Engineer, and the broader Mind Moves project team — while working closely with institutional stakeholders and Data Access Committees at NIH. This role offers the chance to:

• Make a measurable impact on how safely AI systems handling sensitive genomic and health data can be developed and tested.
• Gain hands‑on experience with privacy‑preserving data generation for frontier AI/ML pipelines.
• Operate at the intersection of data engineering, privacy, and federal data governance in a creative, mission‑driven environment.

The contract will include:

• Design and build synthetic data generation pipelines (statistical modeling, generative models, or agent‑based simulation) that replicate the structure and statistical properties of controlled‑access datasets
• Generate realistic synthetic test/dev datasets (e.g., genomic sequence‑style data modeled on dbGaP) to support prototyping, MVP development, and red‑team testing without exposing real participant‑level data
• Apply and tune privacy‑preserving techniques, including differential privacy noise injection, to bound re‑identification and membership‑inference risk
• Validate synthetic data fidelity — statistical distribution matching, utility‑preservation testing, and downstream model performance parity against real data benchmarks
• Assess and document residual privacy risk (e.g., re‑identification, linkage, membership inference) for each synthetic dataset release
• Collaborate with the Red‑Team/Adversarial Security Lead and Biomedical Privacy & Gateway Engineer to supply adversarial and edge‑case synthetic scenarios for testing
• Contribute methodology documentation and data provenance records for review by institutional Data Access Committees (DACs)
• Collaborate with cross‑functional teams across federal agencies and supporting partners

Contractor has the following skills/background:

• Demonstrated experience building synthetic data generation pipelines using statistical modeling, generative models (e.g., GANs, VAEs, diffusion), or agent‑based simulation
• Experience engineering and transforming large‑scale genomic formats (e.g., multi‑sample VCFs, PLINK binary sets, Hail MatrixTables) alongside complex, longitudinal clinical and phenotypic data.
• Advanced proficiency in Python and SQL, with hands‑on experience using synthetic data, privacy, and scientific libraries (e.g., Opacus, Diffprivlib, PyTorch, Hail, Polars, or Spark).
• Data engineering and ETL skills — pipeline design, schema modeling, API integration
• Knowledge of AI/data governance frameworks such as NIST AI RMF and federal (NIH/HHS) compliance requirements preferred
• Background or experience in biomedical, bioinformatics, or life sciences preferred
• Experience taking synthetic data pipelines from proof of concept through to production‑grade, reusable tooling
• Strong communication skills; ability to document methodology and risk assessments for non‑technical and institutional stakeholders
• U.S. work authorization for 1099 contracting; Mind Moves cannot offer sponsorship for this contract
• Must be eligible to obtain and maintain a federal public trust credential / government badge.

Proposal Details

Compensation range: $100-130/hr

Estimated contract duration: September - December

Contract hours: 20-25 hours/week

Work locale: Remote in the US (EST time zone preferred)

Read more about Mind Moves: https://mindmoves.co/