Machine Learning Engineer, Taskrabbit
Outsourcing marketplace for everyday tasks
Job no longer available
Outsourcing marketplace for everyday tasks
1001+ employees
Job no longer available
1001+ employees
Company mission
To transform lives, one task at a time, by connecting millions globally with trusted Taskers every year.
Role
Who you are
- Minimum of an MSc degree in Computer Science, Data Science, or a related field. PhD is a plus
- Solid understanding of machine learning algorithms and techniques, particularly in the context of ranking and recommendation systems
- Proficiency in programming languages such as Python or C++, and experience with ML libraries/frameworks (e.g., PyTorch, scikit-learn, XGBoost)
- Strong knowledge of data processing and manipulation using SQL and/or NoSQL databases
- Experience with large-scale data processing frameworks (e.g., Apache Spark) and distributed computing is desirable
- Familiarity with software engineering principles and best practices, including version control systems (e.g., Git) and agile development methodologies
- Excellent problem-solving skills and the ability to analyze complex data sets to derive actionable insights
- Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment
- Demonstrated ability to work on multiple projects simultaneously, prioritize tasks, and meet deadlines
- Proven track record of delivering high-quality ML solutions
What the job involves
- Machine Learning is a key element in Taskrabbit and we are scaling up our functional teams to provide key insights to drive our business forward
- You will be a member of the Data Group: Machine Learning, Data Science and Data Engineering. We are a force multiplier, owning the data, analysis, and knowledge infrastructure that enables ourselves and our teammates to move faster and smarter
- As a machine learning engineer, you will be working on the development and improvement of our ranking and recommendation models
- You will also drive the innovative solutions for recommendation systems and will work closely with the ML infra engineers to deploy the state-of-the-art algorithms in production
- You will also work with other data scientists and machine learning engineers to ensure that our models are performant, scalable and reliable to be deployed for testing
- Develop and enhance machine learning algorithms for search ranking and recommendation systems, utilizing state-of-the-art techniques and methodologies
- Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to understand business requirements and translate them into effective solutions
- Implement and maintain scalable and efficient systems for data collection, preprocessing, and feature engineering to support the development phases
- Optimize and fine-tune machine learning models to improve their accuracy, efficiency, and scalability
- Stay up-to-date with the latest advancements in the field of machine learning, ranking, and recommendation systems and propose innovative ideas to improve our systems
- Conduct thorough testing and debugging of ML models to ensure their robustness and stability in real-world scenarios
- Document and communicate technical concepts, solutions, and recommendations effectively to both technical and non-technical stakeholders
- Contribute to the development and maintenance of best practices, coding standards, and ML engineering frameworks within the team
Our take
Back in 2011, TaskRabbit took full advantage of a growing trend - that technology enables consumers to do more commerce in their homes than ever before. Its marketplace connects users to "Taskers" that can perform virtually any role customers require, such as heavy lifting and cleaning.
TaskRabbit's product is diverse, with the potential to enter any commerce sector in the world. In 2017, the company was acquired by IKEA, which gave it the resources to undergo a data-driven European expansion which included launching in Germany and France, as well as increasing services in densely-populated UK areas.
By developing internationally, while also emphasising its offerings as a delivery service, the company has set itself up on the world stage. Having continued to grow and expand its offerings, TaskRabbit remains a key player in the gig economy, with every sign that it will continue its successes into the future.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
3% employee growth in 12 months
Company
Funding (2 rounds)
Jul 2012
$13.8m
Dec 2011
$18.8m
Total funding: $32.6m
Company benefits
- Remote first and highly connected
- Employee-covered health care
- 401k with match
- Flexible PTO
- Paid holidays & recharge weeks
- Wellbeing allowance and free access to HeadSpace and Spring Health
- Paid parental leave, adoption assistance, and reproductive health assistance
- Speaker series, career paths, and an annual education allowance
- IKEA discount, Taskrabbit credit, and productivity stipend
Company HQ
Potrero Hill, San Francisco, CA
Leadership
Ania Smith
(CEO)Several years of experience in leadership at companies like Expedia, Uber, Airbnb and Walmart.
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