Senior Machine Learning Engineer, Taskrabbit
$148-200k
Offers bonus
More information about location
2+ days a week in office
Outsourcing marketplace for everyday tasks
Open for applications
Outsourcing marketplace for everyday tasks
1001+ employees
Open for applications
$148-200k
Offers bonus
More information about location
2+ days a week in office
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
- We welcome applicants from a variety of backgrounds and experiences. Below gives you a sense of how we're thinking about what you'll need to be successful in the role
- BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field
- 3+ years of industry experience building and deploying high-quality, production-grade machine learning models and systems
- Strong theoretical knowledge and hands-on experience in machine learning, particularly in areas like search, ranking, recommender systems, or NLP
- Solid software engineering skills with proficiency in one or more programming languages, including Python. The candidate should have experience with popular ML libraries like Scikit-learn, lightgbm, xgboost, TensorFlow, PyTorch, etc
- Proficiency in SQL is also required for writing complex queries and transforming data
- Experience building REST API-based services
- Experience with modern data and ML technologies, such as Docker, Kubernetes, Kafka, Airflow, data warehouses (eg snowflake, redshift or BigQuery), and data lakes
- Familiarity with dbt (Data Build Tool) is a plus for transforming and testing data
- Familiarity with tools for Infrastructure as Code, such as Terraform, and CI/CD pipelines
- Excellent communication skills, with the ability to present complex findings and recommendations clearly to both technical and non-technical audiences
- A passion for quickly learning new technologies and a drive to solve challenging problems
What the job involves
- Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned Senior Machine Learning Engineer to join our team and help shape the future of ML/AI at Taskrabbit
- This is a unique, full-stack role for an individual who is passionate about the entire machine learning lifecycle—from initial research and model development to building the robust infrastructure required to deploy and scale your work
- As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how people discover and connect with home services on the Taskrabbit platform
- You will play a crucial role in advancing our capabilities in areas like search ranking, content discovery, and recommender systems
- You will collaborate closely with data scientists and other engineers to design and implement novel algorithms, and you will partner with software engineers to ensure the scalability, reliability, and optimization of our models in production
- Model Development & Research: Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery
- End-to-End ML Lifecycle: Own the entire lifecycle of ML models, including feature engineering, training, evaluation, deployment, and monitoring
- Infrastructure & Scalability: Build scalable and reliable ML infrastructure and data pipelines that support reproducible feature engineering and machine learning model deployment in real-time, near real-time, and batch processes
- Performance & Quality: Build monitoring services to understand data quality and model performance of complex systems, and collaborate with engineering and science teams to optimize existing algorithms for training and evaluation
- Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and sustainable code, and actively participate in code reviews, documentation, and the full software engineering lifecycle
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
$14m
Dec 2011
$19.2m
Total funding: $33.2m
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.
Salary benchmarks
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