Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 6 and day 70.
From 4,523 similar postings that came down. Coming down is not always a hire.
Employment type in the employer’s posting: SALARIED_FTFrom the employer’s posting
Lead the architectural design and strategic development of high-performance AI and machine learning pipelines for complex enterprise initiatives.
Work with data scientists and researchers to operationalize models, transforming prototypes into resilient, production-grade AI systems that meet stringent business requirements.
Optimize model performance, latency, and cost-efficiency across various cloud and edge deployment targets.
What you will be doing: Lead the architectural design and strategic development of high-performance AI and machine learning pipelines for complex enterprise initiatives. Provide technical leadership, mentorship, and guidance to AI/ML engineers and data scientists, fostering technical excellence and career growth.
Deploy, manage, and scale diverse AI models, including pre-trained models (e.g., LLMs, vision models) and custom ML models, into production environments. Work with data scientists and researchers to operationalize models, transforming prototypes into resilient, production-grade AI systems that meet stringent business requirements. Optimize model performance, latency, and cost-efficiency across various cloud and edge deployment targets.
Work with data scientists and researchers to operationalize models, transforming prototypes into resilient, production-grade AI systems that meet stringent business requirements. Optimize model performance, latency, and cost-efficiency across various cloud and edge deployment targets. Integrate AI/ML solutions with major cloud platforms (AWS, GCP, Azure) and leverage containerization technologies (Docker, Kubernetes) for consistent deployment.
What we need from you: - Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field. Ph.D. is a plus. - 7 to 10 years of progressive experience in machine learning engineering, software development with an ML/AI focus, or a related role.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 6 and day 70.
From 4,523 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Proven technical leadership experience, including mentoring engineers, driving architectural choices, and managing project delivery. - Expert programming skills in Python and proficiency in ML/AI frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Demonstrable, hands-on experience in deploying and fine-tuning advanced pre-trained models, such as Large Language Models (LLMs) or similar Generative AI technologies, into low-latency production environments.
At Pythian, we are experts in strategic database and analytics services, driving digital transformation and operational excellence. Pythian, a multinational company, was founded in 1997 and started by ensuring the reliability and performance of mission-critical databases. We quickly earned a reputation for solving tough data challenges. We were there when the industry moved from on-premises to cloud environments, and as enterprises sought more from their data, we expanded our competencies to include advanced analytics. Today, we empower organizations to embrace transformation and leverage advanced technologies, including AI, to stay competitive. We deliver innovative solutions that meet each client’s data goals and have built strong partnerships with Google Cloud, AWS, Microsoft, Oracle, SAP, and Snowflake. The powerful combination of our extensive expertise in data and cloud and our ability to keep on top of the latest bleeding edge technologies make us the perfect partner to help mid and large-sized businesses transform to stay ahead in today’s rapidly changing digital economy. Why you:
- Optimize model performance, latency, and cost-efficiency across various cloud and edge deployment targets. - Integrate AI/ML solutions with major cloud platforms (AWS, GCP, Azure) and leverage containerization technologies (Docker, Kubernetes) for consistent deployment. - Implement comprehensive MLOps practices, including automated testing, continuous integration/continuous delivery (CI/CD) for models, model versioning, monitoring, and proactive maintenance systems.
- Demonstrable, hands-on experience in deploying and fine-tuning advanced pre-trained models, such as Large Language Models (LLMs) or similar Generative AI technologies, into low-latency production environments. - Extensive experience with cloud platforms (AWS, GCP, Azure) and container orchestration using Docker and Kubernetes. - Proficiency in Data Engineering principles, ETL/ELT processes, and version control systems (e.g., Git).
- Proficiency in Data Engineering principles, ETL/ELT processes, and version control systems (e.g., Git). - Proven experience in orchestrating complex Machine Learning pipelines using open-source tools like Kubeflow, MLflow, or managed cloud services. - Experience in building and optimizing scalable, distributed AI/ML systems.
Complete your application on ats.rippling.com. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed one other Lead AI/ML Engineer job there since September 2026. It is still up.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Why Pythian:
At Pythian, we are experts in strategic database and analytics services, driving digital transformation and operational excellence. Pythian, a multinational company, was founded in 1997 and started by ensuring the reliability and performance of mission-critical databases. We quickly earned a reputation for solving tough data challenges. We were there when the industry moved from on-premises to cloud environments, and as enterprises sought more from their data, we expanded our competencies to include advanced analytics.
Today, we empower organizations to embrace transformation and leverage advanced technologies, including AI, to stay competitive. We deliver innovative solutions that meet each client’s data goals and have built strong partnerships with Google Cloud, AWS, Microsoft, Oracle, SAP, and Snowflake. The powerful combination of our extensive expertise in data and cloud and our ability to keep on top of the latest bleeding edge technologies make us the perfect partner to help mid and large-sized businesses transform to stay ahead in today’s rapidly changing digital economy.
Why you:
As a Lead AI / ML Engineer, you will define the technical vision, strategy, and overall architecture for Artificial Intelligence and Machine Learning solutions. Beyond building robust, scalable AI/ML pipelines, you will lead engineering teams, mentor junior and mid-level engineers, and drive technical decision-making across projects. You will take full ownership of integrating advanced models—including Large Language Models (LLMs) and Generative AI—into enterprise products, partnering closely with executive leadership, product management, and cross-functional engineering teams to deliver impactful business outcomes.
If this is you, and you wonder what it would be like to work at Pythian, reach out to us and find out!
Intrigued to see what a life is like at Pythian? Check out #pythianlife on LinkedIn and follow @loveyourdata on Instagram!
Not the right job for you? Check out what other great jobs Pythian has open around the world! Pythian Careers
What you will be doing:
What we need from you:
What you will receive:
Hiring Disclaimer
AI Disclaimer
Pythian may utilize Enterprise Generative Artificial Intelligence (AI) tools or features throughout its hiring process. These tools help us manage high volumes of applications efficiently and may be employed to review applications, analyze resumes, and assist with other recruitment steps. While Pythian uses AI in its hiring process, it does not substitute for human judgment. Our Talent Acquisition Team reviews all AI-generated recommendations, and the system is subject to regular bias audits to ensure fairness and compliance with all applicable employment and human rights laws. All final hiring decisions are made by, and remain the responsibility of, human decision-makers. By applying for this position, you consent to Pythian’s use of these AI tools in the evaluation of your application. You have the right to request a human review of any solely AI-driven decision or to request an accommodation. Should you require further details regarding the processing of your data, please reach out to us.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Canada
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.