Jobs

    Staff ML Software Engineer - Canada - Salesforce

    Salesforce
    Salesforce Canada

    3 weeks ago

    Default job background
    Description

    Job Description

    About the Team
    Slack is looking for an experienced Staff engineer to join its Core Product organization to help design, develop, and maintain the Search product experience for all Slack entities. The Search product is an integral and compelling feature of Slack as it enables our customers to find and discover messages, channels, people, files, and other entities within their workspaces. It is also of central importance to our efforts around generative AI, helping to build products that are informed by the full wealth of knowledge in our customers' companies. We are seeking a candidate who can continue to evolve our system to be accurate, reliable, performant, and scalable, while helping push us to the cutting edge of search technology, incorporating the latest and greatest developments in the realm of information retrieval.

    Demonstrating your deep experience in leading efforts to research, develop, and deploy pioneering machine learning algorithms, you will improve upon, or create new, ranking systems, associated models, and other tools to power the Search product within Slack. You're a creative problem-solver, passionate about digging into complicated problems and applying your scientific knowledge to collect and analyze data, identify problems and come up with novel methods to address them. Your expertise in working with standard languages like Java, Python, PHP/Hack, and SQL will be critical to enable you to realize and implement your designs. We're a collaborative team who genuinely enjoys working together. You'll be working closely with other software and machine learning engineers to develop the Search product. You'll also be collaborating closely with designers, user researchers, data analysts, product engineers and managers to make Search support the needs of all our users. Slack has a positive, diverse, and supportive culture—we look for people who are curious, inventive, and work to be a little better every single day. In our work together we aim to be inquisitive, humble, hardworking and, above all, collaborative. If this sounds like a good fit for you, we would love to speak with you What you will be doing:
    • Improve Slack's search quality and user experience through optimal query analysis and relevance matching across different searchable entities
    • Conducting applied research in the Search product, you will design and improve on ranking system and models through the analysis of messaging and other searchable entity data
    • Own and evolve the Search system to enable long-term, scalable growth
    • Identify gaps and improvements to existing systems, and contribute to technical roadmap planning
    • Partner with product management to conceptualize and build new features for the Search product
    • Multi-functionally collaborate with other teams to build search functionality for new Slack products
    • Mentor other junior to senior level engineers

    You may be a fit for this role if you have:

    • 5+ years of industry work experience in Machine Learning applied in one or more of the related fields: Ranking, Search Engine, and Recommendation systems
    • Solid hands-on skills in sourcing, cleaning, manipulating, analyzing, visualizing and modeling of complex data sets to identify the essence of problems
    • Demonstrated ability to lead complex projects and guide senior team members
    • Strong problem-identification and solving skills, coupled with an ability to think critically to propose new, or effect change, to improve existing systems and models
    • Excellent communication skills to explain complex technical concepts to senior product, engineering, and executive leadership
    • Strong CS fundamentals in data structures, algorithm design, and statistics
    • Demonstrated experience with programming languages such as Java, JS, Python, etc.
    • Experience contributing to technical architecture discussions to drive technical decisions within your team.
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