Machine Learning Engineer developing ML models and features to enhance Slack’s user experience through AI. Collaborating with cross-functional teams to drive impactful improvements.
Responsibilities
Leveraging machine learning and artificial intelligence subject matter expertise to drive improvements in the Slackbot experience.
Develop ML models supporting ranking, retrieval, and generative AI use-cases.
Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features for our large (and growing!) user base.
Produce high-quality results by leading or contributing heavily to large multi-functional projects that have a significant impact on the business.
Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.
Support in the development of sustainable data collection pipelines and management of ML features.
Assist our skilled support team and operations team in triaging and resolving production issues.
Mentor other engineers and deeply review code.
Improve engineering standards, tooling, and processes.
Requirements
Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.
Built with common ML frameworks like PyTorch, Tensorflow, Keras, XGBoost, or Scikit-learn
Fine tuned LLMs or BERT models.
Experience building batch data processing pipelines with tools like Apache Spark, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.
An analytical and data driven mindset, and know how to measure success with complicated ML/AI products.
Put machine learning models or other data-derived artifacts into production at scale.
Led technical architecture discussions and helped drive technical decisions within the team.
The ability to write understandable, testable code with an eye towards maintainability.
Strong communication skills and you are capable of explaining complex technical concepts to designers, support, and other specialists.
ML Engineer training diffusion models for Hapiko’s voice - activated Stickerbox, which turns kids’ spoken ideas into stickers. Bringing Spin Master characters into production safely and on - model.
Trust & Safety ML Engineer safeguarding Hapiko’s generative - AI sticker printer for children. Owning moderation pipelines, safety evaluations, classifiers, red teaming, and compliance systems.
MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
Senior Data Engineer building cloud - native data and ML platforms for Hive.co’s event - marketing automation products. Owning pipelines, model infrastructure, and audience - data systems at scale.
Senior Machine Learning Engineer building causal and decision systems for CSC Generation’s AI - native omnichannel retail brands. Deploying machine learning that improves pricing and other commercial decisions.
Director leading agentic AI and machine learning products for Instacart’s grocery technology platform. Building retailer solutions and guiding teams from strategy through production deployment.
New - grad software engineer building Quora’s distributed ML platform, model serving, and developer tooling. Supporting Quora’s global knowledge - sharing product with scalable GPU infrastructure.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
Senior Machine Learning Engineer building conversational AI agents and production ML systems. Helping Numa automate automotive dealership service and sales through evaluation - first tooling and infrastructure.