Machine Learning Engineer developing consumer - facing AI features powered by LLMs at Quora. Collaborating with engineers and optimizing production AI systems for enhanced user engagement.
About the role
- Applied ML Engineer working on AI-driven insights at Kaseya. Collaborating with product teams to enhance features with machine learning and data analysis.
Responsibilities
- Explore and analyze data using Python, pandas, and PySpark (or similar tools).
- Use matrix factorization, clustering, dimensionality reduction, and related techniques to understand and prepare data for modeling, and to identify and label latent factors (e.g., user behavior patterns, content/topic clusters, expertise dimensions).
- Create, tune, and productionize ML models for:
- • Categorization / classification
- • Recommendations and similarity
- • Other prediction or ranking tasks that power product features
- Design and implement AI-driven ingest flows that turn unstructured inputs (tickets, emails, forms, messages, logs, etc.) into well-structured data that models and downstream systems can use.
- Build workflows where AI can:
- • Auto-fill or suggest key fields and metadata.
- • Proactively ask users/customers for missing or ambiguous information (e.g., via email or messaging).
- • Surface similar past items or solutions to assist humans in decision-making.
- • Fully handle simple, repetitive “Level 1” style requests end-to-end when safe to do so.
- Work closely with engineers to integrate models and workflows into production systems with proper monitoring, fallbacks, and guardrails.
- Work with multiple product teams to help them identify and scope AI opportunities in their areas.
- Define patterns, templates, and best practices for data ingestion, feature creation, model usage, and evaluation that teams can reuse.
- Serve as a trusted advisor and technical lead:
- • Provide design and architecture guidance on data and ML-heavy features.
- • Join projects to handle the most complex modeling or workflow automation pieces when teams get stuck.
- Mentor and guide junior data/ML engineers and analysts:
- • Conduct code and model reviews.
- • Pair with them on tricky problems.
- • Help them develop good intuitions about metrics, evaluation, and operational reliability.
- Help establish and socialize standards for experimentation, documentation, and responsible AI usage across teams.
Requirements
- 5+ years in data science, ML engineering, or a similar applied role, with a strong record of shipping production data/ML features.
- Strong Python skills and experience with pandas for data analysis.
- Experience with PySpark or other distributed data processing frameworks.
- Solid understanding of ML fundamentals, including:
- • Supervised learning and classification models
- • Matrix factorization / embeddings / latent factor models
- • Feature engineering and model evaluation (offline metrics and online experiments)
- Proficiency with PyTorch (or a similar deep learning framework) and related ML tooling.
- Strong SQL and experience with modern data warehouses / data lakes.
- Comfort working with APIs, microservices, and production integration of ML models, including performance and reliability considerations.
- Experience serving as a technical lead or senior individual contributor across multiple teams or projects.
- Proven ability to translate business problems into data/ML projects, and to clearly explain tradeoffs to non-ML stakeholders.
- Track record of mentoring junior engineers/analysts and improving team practices (e.g., review culture, testing, monitoring).
- Strong communication skills and the ability to drive alignment across product, engineering, and operations.
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Staff Machine Learning Engineer on Merchant team at Pinterest. Leading ML initiatives to enhance merchant quality and improve user shopping experiences.
Machine Learning Engineer at Sumsub building ML solutions combating fraud and identity theft. Work with global teams in a fully remote setting allowing product autonomy.
Associate Deep Learning Engineer implementing deep learning and computer vision algorithms at NBCUniversal. Collaborating with cofounders to meet technical milestones and deploying code on geospatial datasets.
Staff Product Manager leading Vegetation Intelligence at Overstory, harnessing machine learning to enhance utility vegetation management. Overseeing product strategy and development for critical vegetation insights.
Machine Learning Engineering Intern developing innovative AI solutions for contact centers at Cresta. Collaborating with top researchers and engineers in AI to unlock customer experience potential.
MLOps/LLMOps Architect designing AI solutions for a next - gen AI platform in Canada. Collaborating with teams on architecture, deployment, and governance in AI environments.
Staff Deep Learning Engineer at NBCUniversal implementing core algorithms for 2D and 3D media datasets. Collaborating with cofounders and deploying large - scale algorithms for high - fidelity content.
Deep Learning Engineer at NBCUniversal implementing algorithms in computer vision and graphics. Transforming high dimensional data into high - fidelity content using advanced techniques.
Staff MLOps Engineer responsible for building infrastructure for AI/ML at NBCUniversal. Managing large media datasets, deploying models, and automating data pipelines.