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Remote Aws Machine Learning Jobs in Texas (NOW HIRING)

Data Scientist

Dallas, TX · On-site +1

$110K - $130K/yr

Role Overview We're seeking a Data Scientist with hands-on experience in machine learning ... You'll work within our AWS SageMaker Studio environment and collaborate closely with engineering ...

United States (Remote) Interested applicants must reside in one of the following approved states ... AWS certifications (Data, Machine Learning, or Solution Architecture) are a plus * 8 to 12 years of ...

Lead Data Engineer - AWS

Dallas, TX · On-site +1

$101K - $133K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... LLM Ops: Integrate AWS Step Functions and SageMaker Pipelines to automate the fine-tuning and ...

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

Exposure to machine learning pipelines, MLOps concepts, or AI-driven data workflows preferred ... is Hybrid Remote. We offer several comprehensive benefits package including health and life ...

Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest * Distributed computing tools and cloud technology (AWS) QUALIFICATIONS * Degree in Data Science ...

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models ... Familiarity with cloud platforms (AWS, Azure, or GCP) * Experience with modern ML frameworks ...

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Familiarity with cloud platforms (AWS, Azure, or GCP) * Experience with modern ML frameworks ...

Lead AI Engineer - AWS Platform

Dallas, TX · On-site +1

$130K - $190K/yr

Build machine learning models that automate their training, validation, monitoring, and retraining ... Flexible work schedules and hybrid/remote options for eligible positions * Educational assistance ...

Senior DevOps Engineer

Austin, TX · On-site +1

$128K - $165K/yr

Remote * Salary $150k - $200k * Seed Company * Skills: Ansible, Bash, Python, Terraform, Docker ... machine learning architecture. * Have an expert level understanding of Terraform and Ansible in ...

Modeling Scientist

Houston, TX · On-site +1

$100K - $160K/yr

Remote Base Salary Range : $100k - $160k base salary The Modeling Scientist is responsible for ... Working at the intersection of statistics, machine learning, and process-based ecosystem modeling ...

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Remote Aws Machine Learning information

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

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are remote AWS Machine Learning jobs?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

What is the difference between Remote Aws Machine Learning vs Remote Data Scientist?

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are the most commonly searched types of Aws Machine Learning jobs in Texas? The most popular types of Aws Machine Learning jobs in Texas are:
What are popular job titles related to Remote Aws Machine Learning jobs in Texas? For Remote Aws Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Texas look for? The top searched job categories for Remote Aws Machine Learning jobs in Texas are:
What cities in Texas are hiring for Remote Aws Machine Learning jobs? Cities in Texas with the most Remote Aws Machine Learning job openings:
Staff Machine Learning Engineer (Remote)

Staff Machine Learning Engineer (Remote)

SailPoint Technologies Holdings, Inc.

Austin, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 27 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 play a critical role in shaping, building, and scaling SailPoint's AI-powered capabilities. You'll work at the intersection of AI innovation, software engineering, and platform architecture-designing robust, production-grade ML systems that deliver customer insights and intelligent automation across our identity platform.
As a senior technical leader, you'll partner closely with engineering, AI, and product teams to drive innovation, define our ML strategy, and mentor others in applying best practices for scalable, responsible AI.
This is both a hands-on and strategic role. You will lead complex, end-to-end ML initiatives-from model design and experimentation to deployment, monitoring, and continuous improvement-while advancing the evolution of SailPoint's AI platform, data pipelines, and model governance standards.
About the team:
The AI team at SailPoint applies AI and domain expertise to create AI solutions that solve real problems in identity security. We believe the path to success is through meaningful customer outcomes, and we leverage classical ML as well as recent innovations in Generative AI and Graph ML to bring our solutions to SailPoint's core product lines.
Responsibilities
  • Design, implement, and optimize ML models (supervised, unsupervised, and LLM-based) that power both customer-facing and internal product capabilities.
  • Translate AI research and experimental prototypes into scalable, maintainable production systems.
  • Lead technical efforts to improve model accuracy, precision/recall trade-offs, and generalization across diverse regions and customer datasets.
  • Build and enhance ML infrastructure and pipelines for feature extraction, model training, evaluation, deployment, and monitoring.
  • Drive the technical strategy for reproducibility, model versioning, data lineage, and CI/CD automation in ML systems.
  • Collaborate with AI platform and DevOps teams to ensure reliable data access, observability, and efficient use of compute resources.
  • Set technical direction and best practices for ML engineering across the AI organization, influencing architecture and design standards.
  • Mentor and guide engineers in scalable ML design patterns, experimentation frameworks, and software craftsmanship.
  • Partner with product and engineering leaders to prioritize and deliver high-impact AI capabilities aligned with business goals.
  • Work cross-functionally with architecture, platform, and analytics teams to ensure AI components integrate seamlessly across SailPoint's ecosystem.
  • Advance model lifecycle management, AI governance, and responsible AI practices to ensure quality, fairness, and transparency.
  • Communicate complex ML concepts into actionable insights and recommendations for technical and non-technical audiences.
  • Support day-to-day team operations in partnership with TPMs and managers, ensuring alignment and delivery across initiatives.

Requirements:
  • 8+ years of professional experience in machine learning engineering, software development, or a related technical field.
  • Strong programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Proven track record of building and deploying ML models at production scale (cloud-native environments preferred).
  • Deep understanding of data modeling, feature engineering, and statistical analysis.
  • Expertise in data pipelines, ETL, and feature engineering using frameworks like Spark, Airflow, or dbt.
  • Solid knowledge of MLOps practices-including model monitoring, retraining, CI/CD, and experiment tracking.
  • Strong foundation in software engineering best practices: testing, modularization, code review, and observability.
  • Excellent communication and collaboration skills, with demonstrated experience leading cross-functional technical initiatives.

Preferred
  • Experience with LLM-based solutions, embeddings, and retrieval-augmented generation (RAG).
  • Familiarity with identity, security, or enterprise SaaS systems.
  • Experience designing AI platforms or reusable ML services that support multiple product lines.
  • Demonstrated ability to set technical direction, influence architectural decisions, and guide organizational strategy.

Roadmap for success-
30 days:
  • Gain deep understanding of SailPoint's AI vision, architecture, and active ML initiatives.
  • Familiarize with existing data pipelines, environments, and model deployment frameworks.
  • Build relationships with key stakeholders across AI, platform, DevOps, and product teams.
  • Conduct hands-on review of current ML models, data flows, and monitoring systems to identify immediate optimization or reliability gaps.
  • Begin contributing to small improvements or code reviews to gain familiarity with production practices.

90 days:
  • Lead at least one end-to-end ML enhancement or pilot.
  • Establish and document best practices for reproducibility, observability, and CI/CD for ML systems.
  • Mentor junior engineers and support team-wide code quality and experimentation standards.
  • Present a roadmap or proposal for scaling AI components or addressing key technical debt areas.

6 months:
  • Deliver measurable impact on model performance, reliability, or scalability for at least one core AI product.
  • Lead design and implementation of a shared ML service or reusable component (e.g., feature store, inference service, or monitoring framework).
  • Be recognized as a technical go-to for complex ML engineering and architecture decisions.

1 year:
  • Establish SailPoint's ML engineering foundation as robust, scalable, and production-ready across multiple AI initiatives.
  • Drive one or more flagship AI capabilities from prototype to production, with demonstrated business or customer impact.
  • Mentor and elevate other engineers, fostering a culture of technical excellence and continuous learning.
  • Influence long-term AI platform architecture and strategic investment areas as part of the broader AI leadership group.

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

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-mid-max, USD):
$141,300 - $238,124.00
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.