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Applied Ml Engineer Jobs (NOW HIRING)

Senior AI/ML Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Mentor other engineers on ML best practices and code quality What we are looking for * 4+ years of applied ML engineering in production environments * Hands‑on experience with LLMs, fine‑tuning ...

Senior AI/ML Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Mentor other engineers on ML best practices and code quality What we are looking for * 4+ years of applied ML engineering in production environments * Hands-on experience with LLMs, fine-tuning, RAG ...

Senior AI/ML Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Mentor other engineers on ML best practices and code quality What we are looking for * 4+ years of applied ML engineering in production environments * Hands-on experience with LLMs, fine-tuning, RAG ...

Applied Audio ML Engineer

San Francisco, CA · On-site

$122K - $151K/yr

As an Applied ML Engineer, you will build advanced speech and audio models, develop production inference systems, and collaborate with cross-functional teams to enhance model quality.

MS or PhD in CS/EE/Statistics/Applied ML (or BS with strong equivalent experience). • Experience: 5+ years applied ML engineering experience; 2+ years specifically in audio/speech or time-series ML ...

Senior Applied ML Engineer

Seattle, WA · On-site

$118K - $163K/yr

Strong programming skills in Python and hands on experience with modern ML frameworks such as PyTorch or JAX * Strong understanding of LLM post-training techniques, including supervised fine-tuning ...

Senior Applied ML Engineer

Bellevue, WA

$117K - $162K/yr

Strong programming skills in Python and hands on experience with modern ML frameworks such as PyTorch or JAX * Strong understanding of LLM post-training techniques, including supervised fine-tuning ...

Senior Applied ML Engineer

Bellevue, WA · On-site

$117K - $162K/yr

Strong programming skills in Python and hands on experience with modern ML frameworks such as PyTorch or JAX * Strong understanding of LLM post-training techniques, including supervised fine-tuning ...

Engineers on our team touch everything from CUDA kernels to high-performance LLM tracing dashboards ... Required Qualifications * 8+ years of experience in machine learning or applied research, or a PhD ...

Engineers on our team touch everything from CUDA kernels to high-performance LLM tracing dashboards ... Required Qualifications * 8+ years of experience in machine learning or applied research, or a PhD ...

Senior Applied ML Engineer

Sunnyvale, CA

$122K - $168K/yr

Strong programming skills in Python and hands on experience with modern ML frameworks such as PyTorch or JAX * Strong understanding of LLM post-training techniques, including supervised fine-tuning ...

Engineers on our team touch everything from CUDA kernels to high-performance LLM tracing dashboards ... Required Qualifications * 8+ years of experience in machine learning or applied research, or a PhD ...

Lead AI Applied ML Engineer

Jersey City, NJ · On-site

$107K - $140K/yr

You will be responsible for leading a team of 4 to 5 ML engineers. You will work at the intersection of Risk modeling, and NLP architectures, inference systems, regulatory explainability and ...

Lead AI Applied ML Engineer

Jersey City, NJ · On-site

$112K - $147K/yr

You will be responsible for leading a team of 4 to 5 ML engineers. You will work at the intersection of Risk modeling, and NLP architectures, inference systems, regulatory explainability and ...

Showing results 21-40

Applied Ml Engineer information

Are applied ML engineers still in demand?

Applied machine learning engineers are currently in high demand due to the increasing adoption of AI and data-driven solutions across industries. Skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch enhance job prospects, which are expected to remain strong as AI integration continues to grow.

What does an applied machine learning engineer do?

An applied machine learning engineer develops and implements machine learning models to solve real-world problems, often working with large datasets and tools like Python, TensorFlow, or PyTorch. They focus on deploying models into production environments, optimizing performance, and ensuring scalability and reliability of AI solutions.

What cities are hiring for Applied Ml Engineer jobs?

Cities with the most Applied Ml Engineer job openings:

What states have the most Applied Ml Engineer jobs?

States with the most job openings for Applied Ml Engineer jobs include:

What are popular job titles related to Applied Ml Engineer jobs?

For Applied Ml Engineer jobs, the most frequently searched job titles are:

Infographic showing various Applied Ml Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Applied ML Engineer

Mountain View, CA • On-site

SupportFinity™
IT Services • 51 - 200 employees

Other

Posted 10 days ago


Job description

If you’re passionate about tackling some of the hardest problems in AI and contributing to transformational change in enterprise automation, join us at Kognitos to build the future of software.

What You’ll Work On:
  • Efficient Fine-Tuning: Develop innovative methods to optimize resource usage for training and fine-tuning models, ensuring high performance while maintaining efficiency.

  • Agentic Workflows: Advance workflows that allow AI to reason, plan, and execute tasks with reliability and determinism, minimizing errors and runtime surprises.

  • Multimodal Language Models: Work on multimodal use cases, combining text, images, and other data formats, to build adaptive, enterprise-ready automation tools.

  • Scalable AI for Enterprises: Address the needs of enterprises by creating AI solutions that can remove 30% of operational expenses through large-scale adoption.

Responsibilities:
  • Design, implement, and deploy machine learning models focused on agentic workflows and deterministic task execution.

  • Optimize AI systems for multimodal applications, addressing real-world enterprise challenges.

  • Innovate on fine-tuning techniques to maximize resource efficiency and improve model performance.

  • Ensure AI systems are aligned to regulatory policies and deliver consistent business value.

  • Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to deliver impactful solutions.

  • Stay at the cutting edge of AI research, incorporating new advancements into Kognitos’ platform.

Requirements:
  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, or a related field.

  • Proven experience in developing and deploying machine learning models in production environments.

  • Expertise in fine-tuning techniques for large-scale models and optimizing resource usage.

  • Strong intuition working with LLMs

  • Familiarity with multimodal language models and their enterprise applications.

  • Proficiency in Python, TensorFlow, PyTorch, or similar frameworks.

  • Excellent problem-solving skills and the ability to work in a fast-paced, dynamic

Preferred Qualifications:
  • Experience with agentic workflows and multi-agent systems.

  • Knowledge of enterprise automation challenges and opportunities.

  • Prior work in AI for non-consumer use cases, especially in large-scale enterprise environments.

  • Familiarity with cloud platforms and distributed computing frameworks.

Why Join Kognitos?
  • Be part of a cutting-edge company solving some of AI’s hardest problems.

  • Work on impactful projects in a trillion-dollar hyper-automation market.

  • Collaborate with a world-class team of engineers and researchers.

  • Contribute to transformational changes in how enterprises operate.


Final note

You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.

Equal opportunities provider

Kognitos is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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