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Dvc Jobs (NOW HIRING)

Frontier Technology Inc.

AI/ML Engineer

Washington, DC · Remote

$190K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

NAVA Software Solutions

Sr. AI/ML Engineer

Deerfield, IL · On-site

$106K - $145K/yr

DVC, MLflow, Git, CI/CD, containerization (Docker/Kubernetes) * Cloud deployment experience (Azure preferred; AWS or GCP acceptable) * LLM/GenAI experience: building, fine-tuning, or prompting models ...

CCS INC

Lead Gen AI Engineer

Plano, TX · On-site

$85 - $110/hr

Familiarity with CI/CD for ML workflows and versioning tools like MLflow or DVC. * Hands-on experience designing and building cloud-native solutions (preferably on AWS) * Exposure to GenAI tools and ...

Frontier Technology Inc.

$190K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

Bespoke Labs

Data Engineer

Carson City, NV · On-site

$112K - $134K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Sterling Heights, MI · On-site

$107K - $128K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Macon, GA · On-site

$109K - $131K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Brockton, MA · On-site

$115K - $138K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Worcester, MA · On-site

$114K - $137K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Hartford, CT · On-site

$115K - $138K/yr

... DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

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Dvc information

See salary details

$70.5K

$86.3K

$106.5K

How much do dvc jobs pay per year?

As of Jul 14, 2026, the average yearly pay for dvc in the United States is $86,295.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,000.00 and $90,000.00 per year, depending on experience, location, and employer.

What are DVCs?

DVCs, or Data Version Control specialists, are professionals who manage and oversee data versioning using tools like Data Version Control (DVC). They help teams track changes to datasets and machine learning models, ensuring reproducibility and collaboration in data science projects. DVCs work closely with data scientists and engineers to implement data pipelines, handle large datasets, and maintain consistency across multiple experiments. Their expertise is essential in organizations where managing complex data workflows is critical for research and deployment.

What is the difference between Dvc vs Video Editor?

AspectDvcVideo Editor
Required CredentialsHigh school diploma or equivalent; technical training or certification often preferredHigh school diploma; often a degree or certification in film, media, or related field
Work EnvironmentFilm sets, production companies, or broadcast stationsPost-production studios, editing suites, or freelance work
Industry UsageUsed in film, TV, and video production for technical supportUsed in editing and post-production to craft the final video content

While both Dvc and Video Editor work within the video production industry, Dvc primarily handles technical aspects during filming, such as camera operation and equipment setup. In contrast, Video Editors focus on editing footage to create the final product. Understanding these roles helps clarify career paths and job expectations in video production.

How does a Data Version Control (DVC) Engineer typically collaborate with data scientists and machine learning engineers on a project?

A DVC Engineer works closely with data scientists and machine learning engineers to streamline data management, versioning, and reproducibility throughout the machine learning workflow. They help set up and maintain DVC pipelines, ensuring data and model versions are tracked across experiments. Regular communication is essential, as DVC Engineers provide support for integrating DVC into existing workflows, troubleshoot issues, and train team members on best practices. This collaborative effort helps teams maintain consistency, improve efficiency, and facilitate smoother handoffs between stages of model development.

What are the key skills and qualifications needed to thrive as a DVC (Divisional Vice Chancellor), and why are they important?

To thrive as a Divisional Vice Chancellor, you need strong leadership abilities, a background in academia or administration, and typically an advanced degree such as a Ph.D. or Ed.D. Familiarity with university management systems, accreditation processes, and data analysis tools is often required. Exceptional communication, strategic vision, and conflict resolution skills help foster academic excellence and organizational growth. These competencies are critical for effective governance, stakeholder engagement, and advancing the institution’s mission.
More about Dvc jobs
What cities are hiring for Dvc jobs? Cities with the most Dvc job openings:
What states have the most Dvc jobs? States with the most job openings for Dvc jobs include:
What job categories do people searching Dvc jobs look for? The top searched job categories for Dvc jobs are:
Dvc jobs near you
Infographic showing various Dvc job openings in the United States as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, 1% Temporary, and 1% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $86,295 per year, or $41.5 per hour.
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Washington, DC • Remote

$190K - $220K/yr

Full-time

Re-posted 10 days ago

Job description

Overview

FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

Responsibilities
  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.
Education/Qualifications

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

For this role, the compensation range for candidates is $190k-$220k . *Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience. FTI has a location-based compensation structure; there may be a different range for candidates in other locations.

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Employment Type: FULL_TIME

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