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Deep Machine Learning Engineer Jobs (NOW HIRING)

We are looking for a Machine Learning Engineer to help us create artificial intelligence products ... Deep knowledge of math, probability, statistics and algorithms * Ability to write robust code in ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No ... Mastery of Deep Learning fundamentals and statistics underlying Machine Learning. * History of ...

Machine Learning Engineer

San Mateo, CA ยท On-site

$125 - $150/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift ... Design, train, and optimize custom deep learning models that understand CAD workflows and generate ...

NY ยท On-site

$125 - $150/hr

The ideal candidate combines deep ML expertise with strong software engineering skills. They are ... Design and implement machine learning models to solve business problems * Build end-to-end ML ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Hands-on Experience with Deep Learning Models, especially Transformers . * Ability to translate ...

Provide expert insights on machine learning, deep learning, NLP, experimentation, forecasting, and ... Data Engineering experience, including building and maintaining data pipelines and analytical ...

Machine learning, natural language processing, learning-to-rank, online learning, deep learning ... Strong programming skills in Python and Scala required. Experience in other programming languages ...

Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one ... Solid software engineering fundamentals (architecture, Git workflows, testing, code review)

Machine learning, natural language processing, learning-to-rank, online learning, deep learning ... Strong programming skills in Python and Scala required. Experience in other programming languages ...

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How much do deep machine learning engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for deep machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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Staff Machine Learning Engineer

Austin, TX โ€ข On-site

SailPoint Technologies Holdings, Inc.
Software Developmentย โ€ขย 501 - 1,000 employees

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago


Job description

About SailPoint:
SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce and ensuring that workers have the right access to do their job-no more and no less.
Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level of access to the right identities and resources at the right time-matching the scale, velocity, and changing needs of today's cloud-oriented, modern enterprise.
About the Role
As a Staff Machine Learning Engineer, you will be a senior technical leader shaping the next generation of SailPoint's AI-powered capabilities. We are looking for a strong machine learning practitioner with deep machine learning expertise and hands-on experience developing and deploying both classical machine learning solutions and agentic AI systems.
In this role, you will apply machine learning and AI technologies to solve complex identity security challenges, including threat detection, anomaly detection, semantic search, behavioral modeling, and intelligent automation. You'll work across the full lifecycle of AI solutions, from model development and evaluation to scalable deployment and operationalization.
You will also help build and advance Generative AI capabilities by leveraging foundation models and techniques such as retrieval-augmented generation (RAG), fine-tuning, agents, model distillation, and orchestration frameworks. As a senior technical leader, you'll partner closely with engineering, AI, and product teams to define technical strategy, drive innovation, and mentor others in building scalable, reliable, and responsible AI systems.
About the team:
The AI team at SailPoint applies AI and domain expertise to create solutions that solve real problems in identity security. We believe the path to success is through meaningful customer outcomes, and we leverage classical ML, Graph ML, and recent innovations in Generative AI to bring our solutions to SailPoint's core product lines.
Responsibilities:
  • Design, develop, and deploy machine learning and AI-powered solutions to address complex identity security challenges.
  • Lead the design and development of both classical ML capabilities (e.g., anomaly detection, behavioral modeling, semantic search) and agentic AI applications.
  • Evaluate and apply modern AI techniques, including foundation models, embeddings, RAG, agents, and model fine-tuning, to create new product capabilities.
  • Translate AI research and emerging technologies into scalable, production-ready solutions that deliver measurable customer and business impact.
  • Drive technical strategy for AI systems, balancing model quality, reliability, scalability, and operational excellence.
  • Establish engineering best practices for developing, deploying, monitoring, and maintaining ML and AI applications in production.
  • Partner closely with engineering, product, and platform teams to identify high-impact opportunities and deliver AI-driven capabilities.
  • Influence architecture and technical direction across AI initiatives, ensuring solutions integrate seamlessly into SailPoint's ecosystem.
  • Advance AI governance, evaluation, observability, and responsible AI practices to ensure quality, safety, and trustworthiness.
  • Mentor engineers and contribute to a culture of technical excellence, innovation, and continuous learning.
  • Drive technical alignment across AI initiatives and guide critical architectural and engineering decisions.

Requirements:
  • 8+ years of professional experience in machine learning, AI, or a related technical field.
  • Deep machine learning expertise with a proven track record of building and deploying production ML systems, along with experience developing agentic AI applications.
  • Proven experience applying techniques such as anomaly detection, semantic search, embeddings, similarity measurement, classification, or ranking to real-world problems.
  • Experience with Generative AI technologies, including LLMs, RAG, fine-tuning, prompt engineering, agentic AI frameworks (A2A, LangGraph, MCP), model evaluation, and guardrails.
  • Strong programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Deep understanding of data modeling, feature engineering, statistical analysis, experimentation, and model evaluation.
  • Proven experience building and deploying ML systems in production and operating them at scale.
  • Strong software engineering fundamentals, including testing, modular design, code reviews, observability, and operational excellence.
  • Solid understanding of MLOps practices, including CI/CD, experiment tracking, model monitoring, and retraining strategies.
  • Excellent communication and collaboration skills, with experience leading cross-functional technical initiatives and influencing technical direction.
  • Bachelor's degree in Computer Science or a related field.

Preferred
  • Experience in cybersecurity, identity, or enterprise SaaS domains.
  • Deep expertise and a strong track record in one or more of the following areas: NLP, behavioral modeling, time series modeling, graph ML, search, or recommendation systems.
  • Demonstrated experience designing and deploying AI agents, multi-agent workflows, and autonomous systems in production environments.
  • Proven ability to define technical strategy, influence architecture decisions, and drive adoption of AI/ML technologies across teams.
  • Experience building and operating large-scale cloud-native ML and AI systems.
  • Strong track record of delivering measurable business impact through machine learning and AI solutions.

Roadmap for success-
30 days:
  • Gain a deep understanding of SailPoint's AI vision, architecture, and key AI initiatives across both classical ML and Generative AI.
  • Become familiar with the AI platform, data pipelines, model serving infrastructure, and deployment frameworks.
  • Build relationships with key stakeholders across AI, engineering, platform, and product teams.
  • Review existing ML and AI systems, including models, data flows, evaluation frameworks, and operational processes.
  • Begin contributing through code reviews, design discussions, and targeted improvements.

90 days:
  • Lead or significantly contribute to an end-to-end AI initiative, model enhancement, or prototype.
  • Develop or evaluate an AI agent or AI-powered workflow using existing models and platform capabilities.
  • Establish familiarity with our standards for experimentation, reproducibility, observability, and operational excellence.
  • Begin mentoring team members and contributing to technical direction.

6 months:
  • Deliver measurable impact through a production ML or GenAI-powered capability.
  • Drive improvements to AI pipelines, model evaluation, deployment processes, and operational reliability.
  • Partner with product and engineering teams to identify and prioritize new opportunities for AI-driven innovation.
  • Become a trusted technical leader for ML, GenAI, and agentic system design decisions.

1 year:
  • Lead the delivery of one or more strategic AI capabilities from concept to production, with measurable customer or business impact.
  • Influence SailPoint's long-term AI strategy, architecture, and investment priorities.
  • Establish best practices for building, evaluating, and operating both traditional ML and agentic AI systems at scale, helping define SailPoint's long-term approach to AI-powered products.
  • Drive adoption of emerging AI technologies, including foundation models, agents, orchestration frameworks, and model optimization techniques.
  • Mentor and elevate other engineers while fostering a culture of technical excellence, innovation, and responsible AI development.

The Tech Stack (if applicable):
  • Core Programming: SQL, Python, Shell/Bash, Go
  • Cloud Platform: AWS (SageMaker, Bedrock)
  • Data: Snowflake, DBT, Kafka, Airflow, Iceberg, AWS Glue, Feast
  • CI/CD: Cloudbees, Jenkins

SailPoint is an equal opportunity employer and we welcome everyone to our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Benefits and Compensation listed vary based on the location of your employment and the nature of your employment with SailPoint.
As a part of the total compensation package, this role may be eligible for the SailPoint Corporate Bonus Plan or a role-specific commission, along with potential eligibility for equity participation. SailPoint maintains broad salary ranges for its roles to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect SailPoint's differing products, industries, and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. We estimate the base salary, for US-based employees, will be in this range from (min-max, USD):
$149,200 - $251,576.00
Base salaries for employees based in other locations are competitive for the employee's home location.
Benefits Overview
1. Health and wellness coverage: Medical, dental, and vision insurance
2. Disability coverage: Short-term and long-term disability
3. Life protection: Life insurance and Accidental Death & Dismemberment (AD&D)
4. Additional life coverage options: Supplemental life insurance for employees, spouses, and children
5. Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account
6. Financial security: 401(k) Savings and Investment Plan with company matching
7. Time off benefits: Flexible vacation policy
8. Holidays: 8 paid holidays annually
9. Sick leave
10. Parental support: Paid parental leave
11. Employee Assistance Program (EAP) and Care Counselors
12. Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options
13. Health Savings Account (HSA) with employer contribution
SailPoint is an equal opportunity employer and we welcome all qualified candidates to apply to join our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable law.
Alternative methods of applying for employment are available to individuals unable to submit an application through this site because of a disability. Contact applicationassistance@sailpoint.com or mail to 11120 Four Points Dr, Suite 100, Austin, TX 78726, to discuss reasonable accommodations. NOTE: Any unsolicited resumes sent by candidates or agencies to this email will not be considered for current openings at SailPoint.