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Remote Dpo Jobs (NOW HIRING)

logcat.ai

Member of Technical Staff, Applied AI

A note on location Remote, with at least four hours of overlap with Pacific or IST. We don't track ... Preference optimization (DPO/GRPO-style) and structured-output / function-calling fine-tunes. * On ...

Weekday AI

Corporate Treasury Expert

$2.0K/wk

DPO * DIO * Cash conversion cycle * Evaluate bank fees against services received and identify ... Fully remote * Flexible project-based engagement * Self-contained corporate treasury exercises

Lattice

Engineering Manager, AI

$187K - $234K/yr

Familiarity with advanced AI optimization techniques such as Direct Preference Optimization (DPO ... teams. #LI-remote The estimated annual cash salary for this role is $187,500 - $234,500. This ...

Lattice

Engineering Manager, AI

$187K - $234K/yr

Familiarity with advanced AI optimization techniques such as Direct Preference Optimization (DPO ... teams. #LI-remote The estimated annual cash salary for this role is $187,500 - $234,500. This ...

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Remote Dpo information

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$39K

$77.4K

$121.5K

How much do remote dpo jobs pay per year?

As of Sep 15, 2026, the average yearly pay for remote dpo in the United States is $77,439.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,500.00 and $89,000.00 per year, depending on experience, location, and employer.

What is a remote DPO?

A Remote DPO, or Data Protection Officer, is a professional who oversees an organization's data protection strategies and ensures compliance with privacy laws such as the GDPR, while working remotely rather than on-site. Remote DPOs advise on data processing activities, monitor compliance, and serve as a point of contact for data subjects and regulatory authorities. They use digital tools to communicate, conduct audits, and manage data protection tasks from any location. This role is especially valuable for companies operating internationally or with distributed teams.

What are the key skills and qualifications needed to thrive as a remote DPO?

To thrive as a Remote DPO, you need a deep understanding of data protection laws (like GDPR), risk management, and compliance, typically supported by a relevant degree or professional certification (such as CIPP/E or CIPM). Familiarity with privacy management software, data mapping tools, and incident response systems is crucial. Strong communication, problem-solving, and ethical judgment are essential soft skills for advising stakeholders and ensuring regulatory adherence. These skills and qualities are vital to safeguard sensitive data, maintain compliance, and build trust in remote or digital-first environments.

How does a remote DPO typically collaborate with cross-functional teams while ensuring data privacy compliance?

As a Remote DPO, collaboration with cross-functional teams—such as IT, legal, HR, and marketing—is essential to ensure data privacy requirements are integrated into all business processes. You’ll frequently participate in virtual meetings, review data processing activities, and provide guidance on privacy policies and risk assessments. Effective communication skills and a proactive approach are key, as you’ll often need to interpret complex regulations for different departments and ensure ongoing staff training. Despite being remote, building strong relationships and maintaining clear documentation are critical to successfully embedding a privacy-first culture across the organization.

What is the difference between Remote Dpo vs Data Privacy Analyst?

AspectRemote DpoData Privacy Analyst
Required CredentialsGDPR certification, legal or privacy backgroundData protection certifications, analytical skills
Work EnvironmentRemote, compliance-focusedRemote or on-site, data analysis and reporting
Industry UsageLegal, healthcare, finance, techTech, finance, healthcare, consulting

The Remote Dpo primarily oversees data protection compliance and legal requirements, often requiring legal or privacy certifications. In contrast, a Data Privacy Analyst focuses on analyzing data practices, ensuring privacy policies are followed, and may not need legal credentials. Both roles can be remote and are vital in industries handling sensitive data, but the Dpo has a broader compliance and legal oversight scope.

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What cities are hiring for Remote Dpo jobs?

Cities with the most Remote Dpo job openings:

What are the most commonly searched types of Dpo jobs?

The most popular types of Dpo jobs are:

What states have the most Remote Dpo jobs?

States with the most job openings for Remote Dpo jobs include:

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For Remote Dpo jobs, the most frequently searched job titles are:

Infographic showing various Remote Dpo job openings in the United States as of September 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $77,439 per year, or $37.2 per hour.

Member of Technical Staff, Applied AI

Remote

logcat.ai
See more jobs at logcat.aiexternal

Full-time

Medical

Re-posted 29 days ago

Job description

logcat.ai is the AI engineering layer for the operating-system stack. We build agentic systems for Linux and Android devices: we ingest the diagnostic artifacts a device emits (bugreports, logcat, dmesg, modem traces, ramdumps, perfetto, pcap, CAN) and help device makers diagnose, remediate, test, and author features across their OS stack, grounded in their own BSP. Think Datadog and Cursor combined for the OS layer. A VC-backed startup with a small, senior team - you work directly with the founders.
We recently raised a $2.55M pre-seed. The product is scaling and the customer list is growing. The team is still small, so you'll own what you build.
Own the engine that turns every investigation into a compounding asset: the more the platform runs, the sharper it gets. This is applied ML systems, not research. If your goal is training foundation models from scratch and publishing, this is not the seat.
A note on location
Remote, with at least four hours of overlap with Pacific or IST. We don't track hours. We ask for the overlap because a lot of this work is debugging together in real time, and that doesn't work across a twelve-hour gap. If you're in Seattle or Bengaluru, we'd like to meet in person now and then. It isn't a requirement.
The bar
  • 10+ years of relevant engineering experience.
  • Production ML systems experience end to end: data pipelines, fine-tuning, eval, deployment.
  • Hands-on fine-tuning and distillation with open-weight models (Qwen, Llama-class).
  • Eval harness design for correctness-sensitive tasks, including trajectory-level evals for agentic and tool-use systems.
  • Inference deployment and scaling (vLLM or equivalent) on managed platforms.
  • Proficient in day-to-day work with CLI-based AI coding tools like Claude Code (or an equivalent). It's how the team operates, not a nice-to-have.

What you'll do
  • Instrument the product so every investigation, especially human-corrected ones, becomes structured training data.
  • Build the eval harness for diagnostic accuracy. Root-cause correctness has to be measured, not eyeballed.
  • Distill expensive deep-investigation runs into small, fine-tuned models that hold the quality bar at a fraction of the cost.
  • Deploy inference, including on-prem and airgapped SLMs for customers whose logs cannot leave their environment.

Bonus
  • Agent or tool-use systems.
  • Preference optimization (DPO/GRPO-style) and structured-output / function-calling fine-tunes.
  • On-prem or airgapped model deployment.
  • Retrieval over large heterogeneous corpora.
  • Systems or infra background.

What we offer you
  • A front seat as we scale. Customer calls, the roadmap, the pipeline, how the company is actually doing.
  • Top-of-market salary and founding equity. You'll own a piece of what you build.
  • The AI tools you need. We use AI across writing code, reviewing it, research, ops, and internal tooling. If something would help you work better, we'll get it.
  • Early ownership, and full visibility. We move fast, and you'll help decide where.
  • Comprehensive medical insurance for you and your family.
  • Start-up perks and flexible time off, the kind people actually take.
  • A small team that's easy to work with. People here like solving hard problems and helping each other out.

What to expect after you apply
  • Screening call with Head of People & Business Operations
  • Technical conversation with Co-founder/ Head of Engineering
  • Technical exercise with Co-founder/ Head of Engineering
  • Final conversation with CEO
  • References, then offer

In your application, tell us what you'd own here, and the hardest thing you've shipped in this domain.

Apply