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.
Machine Learning Resident for Theragraph involved in developing solutions for health datasets. Collaborating in a cross - functional team under the mentorship of an Amii Scientist.
Senior ML Engineer leading the scaling and innovation of machine learning initiatives at Wisedocs. Collaborating with other engineers to integrate the ML system into the platform for insurance tech.
Lead ML Engineer developing scalable data pipelines and ML systems for Newfold Digital. Collaborate with cross - functional teams using Python, SQL, and cloud ML platforms in an applied ML environment.
Senior Machine Learning Engineer designing and optimizing ML/AI systems for digital forensic tools. Collaborating with cross - functional teams to lead initiatives and drive innovation in digital investigations.
Senior MLOps Engineer focusing on applied MLOps for CreatorIQ, bridging data science and production - grade efficiency. Responsible for annotation workflows and cost - efficient model evaluation.
Senior AI/ML Engineer leading design and deployment of high - impact AI solutions at CloudWerx. Bridging predictive modeling with next - generation Agentic AI to solve client challenges.
Machine Learning Resident developing AI - assisted tools for geotechnical site characterization. Involves collaboration with scientists and engineers to develop predictive ML models.
Machine Learning Resident at Hines Health Services focusing on AI - driven medical workforce solutions. Supporting the development of scalable, AI - powered recruitment platforms over a 6 - month residency.
Software Engineer, Machine Learning developing next - generation AI technologies for clinical trial platforms. Building scalable data pipelines, optimizing model performance, and collaborating with cross - functional teams in a hybrid setting.
Senior Machine Learning Engineer at BenchSci focusing on developing machine learning models for biomedical applications. Collaborating with a team to enhance scientific experiments through AI - driven solutions.