About the Role:

The Machine Learning team at Tubi drives the innovation behind personalized user experiences.  With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming.

We are seeking a highly skilled Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions.

What You'll Do:

• Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience
• Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas
• Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
• Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences.
• Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement

Your Background:

• 8+ years of industry experience building production Machine Learning systems
• MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field
• Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
• Proficiency in building and deploying full-stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
• Solid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning.
• Ability to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutions.

#LI-Hybrid #LI-SC1

About the Job

At BuildOps, we’re building a groundbreaking software solution designed to empower today’s commercial contractors. From service management to project execution, we’re reimagining how our customers operate. Our team thrives on ambition, innovation, and collaboration—qualities we look for in every new hire.

As our Founding Engineer, Agentic Business Transformation, you will embed directly within business functions across the organization, deeply understand how teams operate today, and fundamentally reimagine how they should operate tomorrow. This is not about bolting automation onto existing processes; it's about redesigning how work gets done with agentic tooling transforming (and eliminating) workflows. You will partner with leaders across GTM and G&A to surface high-impact opportunities, architect intelligent solutions, and deliver measurable gains in productivity, output quality, and the experiences we deliver to our customers and employees. You will define what "AI-native operations" looks like inside a high-growth B2B SaaS company—well before most companies have even started asking the question. This is a high visibility role and will involve daily contact with the CEO, Chief of Staff, Chief Revenue Officer, and other members of the BuildOps Executive Leadership Team (ELT). 

ROLES AND RESPONSIBILITIES 

• Embed within internal business functions, including Revenue, RevOps, Customer Success, Customer Support, Finance, People, and Talent, to develop a deep, firsthand understanding of current workflows, pain points, and decision-making processes 
• Conduct structured discovery, shadowing teams, interviewing stakeholders, and mapping end-to-end processes, to identify where AI can eliminate, redesign, or dramatically accelerate work 
• Reimagine workflows from first principles rather than automating existing steps; challenge assumptions about what requires human involvement and what doesn't 
• Design, build, and deploy AI-powered automations, agents, and internal tools that reduce time spent on repetitive, low-value-add tasks while improving the quality and consistency of outputs 
• Integrate large language models, agentic frameworks, and automation platforms into production-grade internal workflows with appropriate guardrails, error handling, and human-in-the-loop checkpoints 
• Measure everything: establish baselines before intervention, track adoption and usage patterns post-deployment, and quantify productivity impact in terms of hours saved, error rates reduced, and cycle times compressed 
• Serve as a trusted advisor to functional leaders on what AI can and cannot do for their teams; translate business problems into technical solutions and technical constraints into business language 
• Stay abreast of the rapidly evolving AI tooling landscape (e.g., LLM capabilities, orchestration frameworks, RPA-to-AI convergence, no-code/low-code platforms) and calibrate our internal stack accordingly 
• Build reusable patterns, templates, and playbooks so that successful automations in one function can be adapted and scaled across others 
• Collaborate closely with the engineering and product organizations to ensure internal automation efforts align with our broader technology strategy and do not create shadow IT risk 

QUALIFICATIONS 

• 5+ years of professional experience building automations, intelligent workflows, or AI-powered solutions in a business context—whether that foundation was in robotic process automation, software engineering, solutions engineering, or applied AI 
• Demonstrated ability to work directly with non-technical business teams: you have spent meaningful time understanding how people actually work before designing what to build 
• Hands-on experience with modern AI tooling, including large language models (e.g., Claude, GPT), prompt engineering, and at least one orchestration or agentic framework (e.g., LangChain, CrewAI, n8n, or similar) 
• Strong scripting and integration skills with the ability to connect APIs, build data pipelines, and stand up end-to-end workflows in production—not just prototypes
• Track record of automating processes that previously required human judgment—not just rules-based tasks, but work involving unstructured data, natural language inputs, or contextual decision-making
• Process-oriented mindset: you naturally decompose complex workflows into discrete steps, identify bottlenecks, and think in terms of inputs, outputs, and handoffs
• Comfort operating with high autonomy in a fast-moving environment; you don't wait to be told what to build — you go find the highest-leverage problem and propose a solution
• Excellent communication skills: you can present a business case to the CEO, C-suite executives, or VPs, run a discovery session with an ops team, and write clear documentation for a workflow you've built
• Experience in B2B SaaS, vertical software, or a similarly complex operational environment is a strong plus
• Familiarity with process mining, workflow analytics, or structured methodologies for identifying automation candidates (e.g., lean, six sigma, or consulting-style process improvement) is a plus

COMPENSATION

• [$188,000 to $273,000 base] + bonus opportunity (LA or SF Hub)