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Remote Machine Learning Postdoc Jobs in Santa Clara, CA

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Remote Machine Learning Postdoc information

Is ML a high paying job?

Machine learning postdoctoral positions are generally well-paid compared to many academic roles, with salaries often ranging from $60,000 to over $100,000 annually depending on experience, location, and funding. These roles typically require strong programming skills in Python or R and knowledge of algorithms and data analysis, which can contribute to higher compensation levels.

Is a PhD in ML worth it?

A PhD in machine learning can enhance qualifications for a remote machine learning postdoc position, often leading to higher-level research opportunities and increased earning potential. However, it requires significant time investment and may not be necessary for industry roles that value practical skills and experience with tools like Python and TensorFlow. The decision depends on career goals and the specific requirements of the desired position.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Postdoc, and why are they important?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

Is a postdoc harder than a PhD?

A remote machine learning postdoc typically involves more specialized research, higher expectations for independence, and often requires advanced skills in programming and data analysis. While a PhD focuses on completing a dissertation and gaining foundational expertise, a postdoc emphasizes producing publishable research and may involve longer hours and greater responsibility, making it generally more demanding in terms of research output and expertise. However, the difficulty varies based on individual experience and research environment.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

Do you need H-1B for postdoc?

A remote machine learning postdoctoral position typically does not require H-1B sponsorship if the candidate is already authorized to work in the country, such as through a visa or citizenship. However, international candidates may need H-1B or other work visas depending on the employer and local immigration laws. Employers often sponsor visas for postdocs to comply with legal requirements and facilitate employment.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
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Remote Machine Learning Postdoc jobs near you

AI & Machine Learning Engineer

Sustainable Talent

Santa Clara, CA • On-site, Remote

$90 - $130/hr

Full-time

Re-posted 8 days ago

Job description

Sustainable Talent is partnering with Nvidia a global leader who's been transforming computer graphics, PC gaming, and accelerated computing for over 25 years. We are looking for Generative AI Security Engineer to support our client's team based out of in Santa Clara, CA with remote/ hybrid work options.

This is a full-time (W-2) contract role. We offer competitive pay $90/hr - $130/hr based on factors like experience, education, location, etc. and provide full benefits, PTO, and amazing company culture!

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams, focused on AI Safety for LLMs, including multi-lingual, multi-modal, and reasoning models. We value expertise in data science paired with a robust data engineering foundation. This role is directed at assessing, and improving the safety and inclusivity of our LLM models in a scalable fashion. We seek someone proficient in programming and scripting for comprehensive data manipulation, analysis, and model fine-tuning. We believe in proactive problem-solving, minimal supervision, and being exceptional teammates who collaborate, think, and learn as one unit. Let's make a difference together!

What you'll be doing:

  • Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness. These LLM models can be txt-to-txt or multimodal-to-txt.
  • Develop datasets for training LLM models with SFT and RL techniques, for Content Safety, ML Fairness, Security and more.
  • Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems.
  • Define and track key metrics for responsible LLM behavior and usage.
  • Follow the best practices of automation, monitoring, scale, safety.
  • Contribute to our repositories and develop safety tools to help ML teams be more effective.
  • Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets.
  • Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.
  • Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

What we need to see:

  • Bachelor's or Master's Degree in Computer Science or related field or equivalent experience.
  • 2+ years of work experience as a Machine Learning Engineer or Deep Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions.
  • Strong programming skills in languages such as Python. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Proficiency in data manipulation, analysis, and visualization using tools like NumPy and pandas.
  • Deep understanding of machine learning algorithms, statistical models, and data structures.
  • Familiarity with software development practices and version control systems (e.g., Git).
  • Good at problem solving and analytical ability.
  • Excellent collaboration and communication skills.

Ways to stand out from the crowd:

  • Experience with GenAI Security including Prompt Injection Stability, Model Extraction, Confidentiality/Data Extraction, Integrity, Availability and Adversarial Robustness.
  • Experience with one or more of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.
  • Experience with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs (Vision Language Model) or any-to-text
  • Experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance.
  • Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research and publication experience.

Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.

Apply