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Adaptive Ml Jobs (NOW HIRING)

Adaption

Applied ML Engineer

San Francisco, CA · On-site

Lead the design and implementation of efficient, adaptive ML systems across real production environments and varied customer tech stacks. * Own the Outcome: You're not handing off a deck - you're a ...

Webai

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.

Agile Defense

ML Engineer

Omaha, NE · On-site

Our vision is to bring adaptive innovation to support our nation's most important missions through ... ML Engineer Location: Omaha, NE Clearance Level: Active DoD Top Secret Overview: At Agile Defense ...

Agile Defense

ML Engineer

Omaha, NE

Our vision is to bring adaptive innovation to support our nation's most important missions through ... ML Engineer Location: Omaha, NE Clearance Level: Active DoD Top Secret Overview: At Agile Defense ...

Agile Defense

ML Engineer

Omaha, NE

Our vision is to bring adaptive innovation to support our nation's most important missions through ... ML Engineer Location: Omaha, NE Clearance Level: Active DoD Top Secret Overview: At Agile Defense ...

webAI Inc

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.

webAI Inc

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.

Clera

AI/ML Engineer

San Francisco, CA

$150K - $250K/yr

As an AI/ML Engineer, you'll shape the future of engineering automation by building AI that thinks ... From adaptive solvers and reduced-order modeling to generative design and real-time validation ...

Clera

AI/ML Engineer

San Francisco, CA · On-site

$150K - $250K/yr

As an AI/ML Engineer, you'll shape the future of engineering automation by building AI that thinks ... From adaptive solvers and reduced-order modeling to generative design and real-time validation ...

Clera

AI/ML Engineer

San Francisco, CA · On-site

$150K - $250K/yr

As an AI/ML Engineer, you'll shape the future of engineering automation by building AI that thinks ... From adaptive solvers and reduced-order modeling to generative design and real-time validation ...

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Adaptive Ml information

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$102.4K

$150K

How much do adaptive ml jobs pay per year?

As of Jun 21, 2026, the average yearly pay for adaptive ml in the United States is $102,439.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $119,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Adaptive Machine Learning Engineer, and why are they important?

To thrive as an Adaptive Machine Learning Engineer, you need strong foundations in machine learning algorithms, data analysis, and programming (often with a degree in computer science or a related field). Familiarity with ML frameworks (such as TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, along with knowledge of adaptive and online learning techniques. Strong problem-solving abilities, creativity, and effective communication skills help you design, iterate, and implement adaptive models that respond to evolving data. These skills ensure that ML solutions can dynamically adjust to new information, maximizing their long-term effectiveness and impact.

What is an Adaptive ML Engineer?

An Adaptive ML Engineer is a professional who designs, develops, and maintains machine learning systems that can adjust and improve their performance dynamically in response to new data or changing environments. These engineers focus on creating algorithms and models that evolve over time, often using techniques like online learning, reinforcement learning, or continual learning. Their work is crucial in applications where static models are insufficient, such as real-time recommendations, autonomous vehicles, and personalized user experiences. Adaptive ML Engineers also ensure that their systems remain robust, accurate, and relevant as data patterns shift.

What are common challenges faced by professionals working in Adaptive Machine Learning roles, and how can they overcome them?

Professionals in Adaptive Machine Learning often encounter challenges such as handling non-stationary data streams, ensuring model stability during continuous updates, and addressing concept drift where data patterns change over time. To overcome these, it's important to implement rigorous monitoring systems, use robust validation techniques, and collaborate closely with data engineering teams to ensure data quality. Staying up to date with the latest research and leveraging online learning frameworks can also help adapt models efficiently and maintain high performance.

What is the difference between Adaptive Ml vs Data Scientist?

AspectAdaptive MlData Scientist
Required CredentialsTypically a degree in Computer Science, Data Science, or related fields; knowledge of machine learning frameworksUsually a degree in Data Science, Statistics, Computer Science, or related fields; strong programming and statistical skills
Work EnvironmentTech companies, AI startups, research labs focusing on machine learning applicationsVaried environments including tech firms, finance, healthcare, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing adaptive machine learning models and AI solutionsUsed across industries for data analysis, predictive modeling, and decision support

Adaptive ML specialists focus on developing and implementing machine learning models that adapt over time, often working on AI systems. Data Scientists analyze data, build models, and generate insights. While both roles require strong technical skills, Adaptive ML roles are more specialized in creating adaptive algorithms, whereas Data Scientists focus on broader data analysis and modeling tasks.

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Adaptive Ml jobs near you

Founding Machine Learning Engineer

Adaptive Security

New York, NY • On-site

$90K - $120K/yr

Full-time

Medical, Retirement, PTO

Posted 8 days ago

Job description

About Adaptive
NVIDIA and OpenAI's only AI cybersecurity investment.
Adaptive is a cybersecurity startup on a mission to stop AI-powered cyberattacks. In December 2025, the company announced an $81M Series B led by NVIDIA and Bain Capital Ventures, with participation from Capital One Ventures, Citi Ventures, and continued support from Andreessen Horowitz (a16z), the OpenAI Startup Fund, and Abstract Ventures. The round marked NVIDIA's first AI cybersecurity investment.
Adaptive was founded by Brian Long and Andrew Jones, repeat entrepreneurs who have built and scaled category-defining companies. Brian and Andrew previously co-founded Attentive, which grew to more than $500M in annual revenue and a $10B+ valuation, and TapCommerce, which was acquired by Twitter. Together, they bring deep experience building high-growth, product-led businesses at massive scale as Adaptive builds the security layer for the AI era.
Trusted by leading banks, technology companies, and healthcare organizations, Adaptive protects teams from emerging threats like deepfakes, smishing, and AI-powered voice scams. With rapid enterprise adoption and a $200B+ market ahead, the company is just getting started.
Role
We are seeking a Founding ML Engineer to define and build Adaptive's ML capabilities. Our products use LLMs and ML models to detect, classify, and respond to cybersecurity threats in real time. The ML problems here are adversarial by nature. Attackers actively evolve to evade detection, labeled data is scarce for novel attack vectors, and models need to operate at production scale with strict latency constraints.
We don't have dedicated ML infrastructure or an ML team today. You'll be building this from the ground up. You will set the technical direction, stand up the infrastructure, and do the hands-on work yourself. You'll hire your first engineers and grow the function as our ML surface area expands this year and beyond.
Compensation
Adaptive has raised $146M from top-tier investors including BCV, a16z, NVIDIA, and OpenAI. Our roadmap depends on standing up an ML function that doesn't yet exist, and we're ready to compensate accordingly. Expect market level compensation and huge ownership over the ML platform from day one.
Responsibilities
  • Define Adaptive's ML strategy: where ML should be applied across our products, what infrastructure we need, and how we should approach build vs. buy decisions.
  • Design and build production ML systems end-to-end - data pipelines, model training, evaluation frameworks, and inference serving.
  • Establish evaluation methodology. Define how we measure model quality, catch regressions, and make data-driven decisions about model changes.
  • Own the strategy for getting the data you need, in the format you need it - what/how to label, how to build feedback loops, and how our models improve over time.
  • Partner with product engineers to integrate ML into the product. You will write production code and work within our existing codebase.
  • Build and lead the ML team as scope grows.

Qualifications
  • 8+ years of experience building ML systems in production, ideally with experience standing up the ML function at an early stage startup or as the senior or lead ML person at a previous company.
  • Strong software engineering fundamentals. You write production-quality code in modern languages (Python, Java, TypeScript) and work within large codebases.
  • Experience with cloud ML infrastructure (AWS SageMaker, Bedrock, Modal, Baseten, or similar).
  • Experience with common ML and data processing frameworks (PyTorch, Tensorflow, Spark)
  • Comfortable working across the stack - infrastructure, backend services, and data systems.
  • Track record of mentoring MLEs and other engineers with observable, clear improvements in those you've worked with.
  • High autonomy. You'll have support and context from leadership, but you're expected to define the path forward and drive it.

Compensation & Benefits:
  • Competitive cash compensation and meaningful stock.
  • Several medical plans to choose from, most covered at 100% by Adaptive.
  • 401k through Vestwell.
  • Unlimited PTO, including winter break from Dec 24 - Jan 1.
  • A fantastic office atmosphere including coffee, espresso, lounge, snacks, whiteboards, and tons of conference space.
  • Rotating choice of 4 free lunch options from local restaurants every day.
  • Expense dinner if you're in the office past 7pm. Expense Uber if you happen to stay past 9pm.

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