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Remote Deep Learning Jobs in Dallas, TX (NOW HIRING)

Harris

(Remote) Support Analyst

Allen, TX · Remote

Develop a deep understanding of Cayenta applications and use that knowledge to troubleshoot ... Is comfortable learning new technologies and adapting to new ways of working. * Can analyze ...

Cayenta

(Remote) Support Analyst

Allen, TX · Remote

Develop a deep understanding of Cayenta applications and use that knowledge to troubleshoot ... Is comfortable learning new technologies and adapting to new ways of working. * Can analyze ...

Directive

B2B Marketing Manager(Remote US)

Dallas, TX · Remote

$80K - $85K/yr

Deep technical knowledge of Strategy, Paid Media, SEO, and CRO for tech companies * Strong SaaS ... Driven to stay ahead of industry trends, including actively learning how AI and automation can ...

SysMind Tech

Remote | SAP ME & MII Consultant

Richardson, TX · On-site +1

$60.25 - $82.25/hr

Tperson ideal candidate will have a deep understanding of SAP Manufacturing solutions, include SAP ... You will be part of a learning culture, where teamwork and collaboration are encouraged, excellence ...

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All JobsDeep Learning JobsRemote Deep Learning JobsRemote Deep Learning Jobs in Dallas, TX

Remote Deep Learning information

See Dallas, TX salary details

$10.9K

$83K

$138.5K

How much do remote deep learning jobs pay per year?

As of Sep 1, 2026, the average yearly pay for remote deep learning in Dallas, TX is $82,982.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,200.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a remote deep learning engineer?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What skills and qualifications are needed to thrive as a remote deep learning engineer?

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.

What are common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

What is the difference between Remote Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

What are the most commonly searched types of Deep Learning jobs in Dallas, TX?

The most popular types of Deep Learning jobs in Dallas, TX are:

What are popular job titles related to Remote Deep Learning jobs in Dallas, TX?

For Remote Deep Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Remote Deep Learning jobs in Dallas, TX look for?

The top searched job categories for Remote Deep Learning jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Remote Deep Learning jobs?

Cities near Dallas, TX with the most Remote Deep Learning job openings:

Remote Deep Learning jobs near you

Ex-MBB Strategy Consultant - AI Training (Remote)

Mindrift

Dallas, TX • Remote

$60/hr

Part-time

Re-posted 15 days ago

Job description

Toloka AI supports frontier model post-training by building domain-specific reinforcement learning environments, tasks, and evaluation frameworks designed by real practitioners.

Mindrift, powered by Toloka - a leading enterprise AI and machine learning data partner since 2014 - connects top domain experts with cutting-edge AI initiatives. Backed by Toloka's deep expertise in scalable data generation, crowd technology, and applied ML systems, Mindrift enables experts to shape how next-generation generative models learn, reason, and perform.

We are launching a Management Consulting domain focused on translating real-world consulting engagements into structured learning environments for advanced AI systems. To do this credibly, we are assembling a team of strategy consultants from top-tier firms who can convert authentic project experience into end-to-end examples - from problem structuring and work planning to analysis, synthesis, and client-ready recommendations.

You will join a growing team of consultants from leading strategy firms shaping how AI learns high-level business reasoning.

Important: This role is exclusively for consultants with direct experience at a top-tier strategy consulting firm. If you do not have hands-on project experience at one of the firms listed below, please do not apply. This requirement ensures the domain is built by practitioners trained to the highest standards of structured problem-solving and client delivery.

Eligible firms: McKinsey & Company, Boston Consulting Group (BCG), Bain & Company, Oliver Wyman, Roland Berger, Monitor Deloitte (Deloitte S&C), EY-Parthenon, Kearney, and Strategy& (PwC).

Who We're Looking For

Consultants with 3+ years of experience at one of the firms listed above, with hands-on project experience in:

  • Structuring ambiguous client problems into workable analytical plans
  • Building financial models, market analyses, or synthesized findings from messy inputs
  • Producing client-ready deliverables under time pressure
  • Forming and defending recommendations under uncertainty

No deep technical background is required - we will onboard you on the lightweight tools involved.

What You'll Do
  • Build realistic consulting project environments - create detailed project scenarios grounded in real engagement dynamics: industry context, financials, constraints, conflicting inputs, and incomplete information.
  • Design structured consulting tasks for AI agents - break projects into discrete tasks that mirror real consulting work: market sizing, commercial due diligence, cost optimization, growth strategy, operational diagnosis, benchmarking, and more.
  • Define evaluation criteria and quality standards - develop grading frameworks, evaluation rubrics, and golden-answer solutions for each task, used to train and calibrate an LLM-based grading system that evaluates AI outputs at scale.

This is a remote, project-based, individual-contributor role focused on analytical design and evaluation.

Skills & Requirements
  • 3+ years at McKinsey, BCG, Bain, Oliver Wyman, Roland Berger, Monitor Deloitte, EY-Parthenon, Kearney, or Strategy&
  • Strong structured problem-solving and hypothesis-driven thinking
  • Ability to translate vague problems into clear analytical steps and deliverables
  • High attention to logical consistency and output quality
  • Independent, self-directed working style
  • Clear written English (B2+)
Compensation

On this project, contributors can earn up to $60 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

For this project, tasks are estimated to require around 25-30 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted. 

Apply