Founding Machine Learning Engineer

Strativ Group; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Strativ Group is seeking a software engineer with hands-on ML experience to turn research into dependable systems. You will design, implement, test, and deploy AI-powered features within existing software, balancing experimentation with production readiness.

You'll work across teams to translate requirements into maintainable solutions, optimize performance, and contribute to architecture decisions that affect reliability and scale.

Qualifications

• Three or more years building software involving ML, AI, or language models.
• Strong Python development skills with ML library experience.
• Practical experience integrating LLMs into software applications.
• Understanding retrieval-augmented generation, model evaluation, and deployment challenges.

Responsibilities

• Develop and deploy ML applications addressing practical business and product challenges.
• Build Python-based services and integrate AI capabilities into existing software systems.
• Experiment with large language models and retrieval techniques to enhance AI-powered applications.
• Create data processing workflows to prepare, transform, and manage information for downstream apps.
• Design testing and evaluation methods to understand model performance and identify improvements.
• Evaluate trade-offs between model quality, latency, infrastructure needs, and operating costs.
• Collaborate with engineers and stakeholders to translate requirements into maintainable solutions.
• Contribute to decisions on architecture, deployment practices, and ML system reliability.
• Keep up with developments in applied AI and assess new techniques for meaningful improvements.

Skills

Python development

ML libraries

LLMs integration

APIs

Data processing

Education

Bachelor's degree in CS/Engineering or related field

Tools

SQL

Cloud infrastructure

Orchestration frameworks

Job description

We're working with an established, technology-led organization investing in the next phase of its machine learning capabilities.

The business is focused on turning advances in AI into practical software applications, with an emphasis on improving how complex processes are managed, how information is used, and how technology can support better decisions.

They're looking to bring in an engineer who combines strong software development skills with hands‑on machine learning experience and an interest in building systems that solve real-world problems.

The Role

This is a hands on engineering position for someone who enjoys taking machine learning concepts beyond experimentation and turning them into dependable software.

You'll work on a range of applied AI projects, contributing to technical design, implementation, testing, and deployment. The work will involve understanding real problems, evaluating different approaches, and building solutions that can be maintained and improved over time.

You'll have room to influence implementation decisions, work closely with other technical specialists, and help shape how machine learning applications are developed and delivered.

The ideal person is comfortable moving between experimentation and production engineering, knows when to use existing models and when a more tailored approach is justified, and cares about the performance of the final product rather than just the underlying technology.

What You'll Be Doing

• Develop and deploy machine learning applications that address practical business and product challenges.
• Build Python‑based services and integrate AI capabilities into existing software systems.
• Experiment with large language models and retrieval techniques to improve the quality and usefulness of AI‑powered applications.
• Develop data processing workflows to prepare, transform, and manage information for downstream applications.
• Design testing and evaluation methods to understand model performance and identify areas for improvement.
• Investigate trade‑offs between model quality, response times, infrastructure requirements, and operating costs.
• Work with engineers and other stakeholders to translate requirements into maintainable technical solutions.
• Contribute to decisions around architecture, deployment practices, and the reliability of machine learning systems.
• Keep up with developments in applied AI and assess where new techniques could deliver meaningful improvements.
• Help improve engineering standards and share knowledge as the team's capabilities grow.

What We're Looking For

• Three or more years of experience building software involving machine learning, AI, or language models.
• Strong Python development skills and experience working with relevant ML libraries.
• Practical experience integrating LLMs into software applications.
• An understanding of retrieval‑augmented generation, model evaluation, and the challenges of deploying AI in production.
• Experience working with APIs, data processing, and software deployment.
• A sound grounding in machine learning fundamentals, statistics, and data handling.
• The ability to investigate unfamiliar problems and make sensible technical trade‑offs.
• A pragmatic engineering mindset, with an emphasis on building, testing, and improving working systems.
• Strong communication skills and the ability to collaborate across technical disciplines.
• Comfortable working in a collaborative, predominantly office‑based environment.

Useful Additional Experience

• Experience with cloud infrastructure and production deployment.
• Familiarity with SQL and modern data storage systems.
• Exposure to model serving, inference performance, or ML operations.
• Experience with conversational systems, speech technology, or multimodal applications.
• Familiarity with orchestration frameworks and integrations between AI models and external tools.
• A degree or postgraduate qualification in a relevant technical discipline.

Why Consider It?

This is an opportunity to join a business investing seriously in applied AI and to work on problems that require both sound engineering and thoughtful experimentation.

You'll have the opportunity to influence technical decisions, take ownership of projects, and work alongside people who care about building useful, reliable software.

The role should appeal to someone who wants meaningful technical responsibility without being restricted to a narrow implementation task or a purely research‑focused remit.

Compensation and Benefits

A competitive package is available, with the final offer dependent on experience, skills, and location.

The wider package and working arrangements will be discussed confidentially during the recruitment process.