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Research Assistant Deep Learning Jobs (NOW HIRING)

Deep Learning Engineer

Palo Alto, CA ยท On-site

$170K - $300K/yr

Keep on top of the latest developments and research in academic CV/DL and decide how we should ... Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs ...

... at least one deep learning framework (PyTorch, Tensorflow, Jax) $19 - $65 an hour Your ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Keep on top of the latest developments and research in academic CV/DL and decide how we should ... Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs ...

Deep Learning Researcher 1900S-2

Billerica, MA ยท Hybrid

$130K - $160K/yr

The Billerica Research & Development team is thriving and growing as we help develop products that ... Develop and evaluate novel deep learning models for complex physical and chemical systems in ...

Deep Learning Researcher 1900S-2

Billerica, MA ยท On-site

$130K - $160K/yr

The Billerica Research & Development team is thriving and growing as we help develop products that ... Develop and evaluate novel deep learning models for complex physical and chemical systems in ...

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How much do research assistant deep learning jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for research assistant deep learning in the United States is $21.91, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $25.48 per hour, depending on experience, location, and employer.

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What are Research Assistant Deep Learning jobs?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

What are the key skills and qualifications needed to thrive as a Research Assistant in Deep Learning, and why are they important?

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What types of projects and daily tasks can a Research Assistant in Deep Learning expect to work on?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.
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What cities are hiring for Research Assistant Deep Learning jobs? Cities with the most Research Assistant Deep Learning job openings:
What states have the most Research Assistant Deep Learning jobs? States with the most job openings for Research Assistant Deep Learning jobs include:

Deep Learning Research Scientist

TalentPros.AI

San Francisco, CA โ€ข On-site, Remote

$250K - $510K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago


Job description

Our mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.


At our firm, we believe the most impactful safety research will require access to frontier AI systems. The most powerful AIs will operate not just on text but also other modes of data, including images, video and audio.ย Such models have potential to augment human creativity and productivity in exciting ways. However, we are very concerned about the risks introduced by powerful multimodal AIs. The Multimodal team builds and studies multimodal models to better understand and mitigate these risks.

Our team works across many parts of a large stack that includes training, inference, system design and data collection. Some of our core focus areas are:


Foundational Research

We develop new architectures for modeling multimodal data and study how they interact with text-only models at scale.


Building Infrastructure

We work on many infrastructure projects including:

  • Complex multimodal reinforcement learning environments.
  • High-performance RPC servers for processing image inputs.
  • Sandboxing infrastructure for securely collecting data.


Data Ingestion

We are more interested in running simple experiments at large scale than smaller complex experiments. This requires access to very large sources of multimodal data. We develop tooling to collect, process and clean multimodal data at scale.

Because we focus on so many areas, the team is looking to work with both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer curve to apply.


You may be a good fit if you:

  • Have significant software engineering experience
  • Are results-oriented, with a bias towards flexibility and impact
  • Pick up slack, even if it goes outside your job description
  • Enjoy pair programming (we love to pair!)
  • Want to learn more about machine learning research
  • Care about the societal impacts of your work


Strong candidates may also have experience with:

  • High performance, large-scale ML systems
  • GPUs, Kubernetes, PyTorch, or OS internals
  • Language modeling with transformers
  • Reinforcement learning
  • Large-scale ETL


The expected salary range for this position is:

Annual Salary: $230,000โ€”$400,000 USD


Logistics

Location-based hybrid policy:ย Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship:ย We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification.ย Not all strong candidates will meet every single qualification as listed.ย Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.


Compensation and Benefits*

Our compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates.

Equityย -ย For eligible roles, equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance.

US Benefitsย -ย The following benefits are for our US-based employees:

  • Optional equity donation matching.
  • Comprehensive health, dental, and vision insurance for you and all your dependents.
  • 401(k) plan with 4% matching.
  • 22 weeks of paid parental leave.
  • Unlimited PTO โ€“ most staff take between 4-6 weeks each year, sometimes more!
  • Stipends for education, home office improvements, commuting, and wellness.
  • Fertility benefits via Carrot.
  • Daily lunches and snacks in our office.
  • Relocation support for those moving to the Bay Area.



* This compensation and benefits information is based on our good faith estimate for this position as of the date of publication and may be modified in the future.ย Employees based outside of the US will receive a different benefits package.ย The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.


How we're different

We believe that the highest-impact AI research will be big science. At our firm, we work as a single cohesive team on just a few large-scale research efforts. And we value impact โ€” advancing our long-term goals of steerable, trustworthy AI โ€” rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.


The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to joining our firm, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.


Come work with us!

We are a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.