What is the salary for this Machine Learing Engineer role?

Salary information is not publicly listed for this position. Apply directly to discuss compensation with Influur.

Where is this Machine Learing Engineer position located?

This is an on-site position at Influur located in San Francisco Bay Area.

How do I apply for this Machine Learing Engineer job at Influur?

Click the 'Apply' button on this page to be redirected to Influur's application portal. Make sure to have your resume ready and tailor your application to highlight relevant experience.

Influur is actively hiring for Engineering roles. Visit the company page to see all open positions and learn more about working at Influur.

Machine Learing Engineer

Influur San Francisco Bay Area Today

engineering

About Influur

Influur is redefining how advertising works — through creators, data, and AI. Our mission is to make influencer marketing as measurable, predictable, and scalable as paid ads — and we're building the tech that powers it. Backed by top-tier investors and trusted by global brands, we're scaling fast across music and culture.

We’re currently developing a next-gen platform that connects artists, brands, and creators through AI-powered matchmaking, campaign automation, and generative tools. If you're a Machine Learning Engineer passionate about building, optimizing, and deploying ML systems at scale, and eager to push the boundaries of AI in advertising, this role is for you.

Your Skillset

Strong experience designing, building, and maintaining end-to-end machine learning systems in production.

Deep understanding of ML algorithms, embeddings, retrieval systems, and evaluation methodologies.

Strong experience with large language models (LLMs), fine-tuning, inference optimization, and agent frameworks.

Expertise in ML infrastructure, including feature stores, vector databases, model serving, and real-time inference pipelines.

Strong Python skills and experience with PyTorch, TensorFlow, FastAPI, NumPy, scikit-learn, and data processing frameworks.

Experience with scalable data pipelines (batch + streaming), including tools like Spark, Kafka, or similar.

Experience implementing ML solutions such as recommendation engines, ranking models, and personalization systems.

Solid understanding of statistical analysis (A/B testing, experimentation, causal inference).

Ability to work closely with engineering teams to productionize ML models with reliability, monitoring, and CI/CD best practices.

You’re the Type Who

Writes clean, reusable, and well-documented code for ML pipelines and distributed systems.

Enjoys experimenting with the latest AI frameworks, ML optimizations, and deployment techniques, turning ideas into fast prototypes.

Partners closely with engineering, product, and data teams to ship ML-powered features that directly impact the user experience.

Thrives in fast-paced, early-stage environments where experimentation, ownership, and rapid iteration matter.

Thinks analytically and solves complex technical problems with efficiency and creativity.

Stays curious about the latest advances in ML infrastructure, LLM optimization, retrieval-augmented systems, and real-time personalization.

Thrives in ambiguity and builds scalable structure from chaos.

What We Offer

• Competitive equity in a venture-backed company shaping the future of music influencer marketing.

• A seat at the table as we redefine how the most iconic record labels, artists, and brands go viral (think Bad Bunny) — with our tech, support, and strategic guidance.

• Access to elite tools, AI copilots, and a team that builds daily at top speed.

• Hybrid flexibility + top-tier health benefits.