Machine Learning Engineer - Applied / Product (Multiple Positions & Levels)
WFA Digital Insight
The demand for machine learning specialists has surged, with a 25% increase in job postings over the past year. As companies like Yobi democratize AI, professionals with a strong background in machine learning and product intuition are in high demand. With the global AI market expected to reach
Job Description
About the Role
Yobi is seeking a highly skilled Machine Learning Engineer to join its Applications team, where you will play a crucial role in bringing the value of user-behavioral foundation models to market. This involves developing scalable, highly profitable products with machine learning at their core. The Applications products are essential to Yobi's success, as they provide the foundation for the company's R&D, power continuous experimentation and improvement, and offer significant data for enhancing core embeddings.As a Machine Learning Engineer on this team, your primary focus will be on the models, metrics, pipelines, systems, and services that power and deliver excellence via Yobi's Applications products. This role involves a significant degree of 0-to-1 development and requires close collaboration with the Product team, core signals Machine Learning Engineers, and leveraging your expertise and insight in building holistic ML-powered products.
The team at Yobi is committed to ethical AI practices and is making waves in the industry with its unique approach to democratizing AI. With partnerships with Microsoft and Databricks, and a world-class team of Machine Learning experts, Yobi offers a dynamic and innovative environment for professionals looking to make a real impact.
What You Will Do
- Develop and deploy machine learning models that drive business results and improve product performance
- Collaborate with cross-functional teams, including Product, Engineering, and Design to identify opportunities for machine learning applications
- Design, implement, and maintain large-scale data pipelines and architectures to support machine learning workflows
- Work on the development of novel machine learning algorithms and techniques to solve complex problems
- Participate in code reviews and contribute to the improvement of the codebase
- Stay up-to-date with industry trends and advancements in machine learning and AI
- Contribute to the development of technical roadmaps and strategy for machine learning applications
- Work closely with the Product team to integrate machine learning models into product features
- Develop and maintain technical documentation for machine learning models and systems
What We Are Looking For
- Strong background in machine learning, with experience in developing and deploying models
- Excellent programming skills in languages such as Python, Scala, or similar
- Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn
- Strong understanding of data structures, algorithms, and software design patterns
- Experience with data pipelines, architectures, and workflows
- Strong collaboration and communication skills, with the ability to work effectively with cross-functional teams
- Experience with cloud-based technologies, such as AWS or GCP
- Strong problem-solving skills, with the ability to debug complex issues
Nice to Have
- Experience with AdTech and product intuition for the space
- Knowledge of recommender systems, personalization, or other consumer-facing ML applications
- Experience with orchestration tools, such as Airflow, and build systems, such as Bazel
- Experience with CI/CD pipelines and version control systems, such as Git
- Experience with SQL and data computation backends, such as Spark
Benefits and Perks
- Competitive base salary and bonus structure
- Meaningful equity and financial upside
- Health, Dental, and Vision insurance
- Flexible PTO and remote work arrangements
- 401k plan and retirement benefits
- Opportunities for professional growth and development
- Access to cutting-edge technologies and innovative projects
- Collaborative and dynamic work environment
How to Stand Out
- Develop a strong portfolio that showcases your machine learning projects and experience, including any personal projects or contributions to open-source repositories.
- Highlight your understanding of machine learning concepts and algorithms, and be prepared to explain them in simple terms during the interview process.
- Show a willingness to learn and adapt to new technologies and frameworks, and express your enthusiasm for staying up-to-date with industry trends and advancements.
- Prepare to discuss your experience with data pipelines, architectures, and workflows, and be ready to provide examples of how you've optimized machine learning workflows in the past.
- Don't be afraid to ask questions during the interview process, such as what a typical day looks like in the role, or what opportunities there are for professional growth and development.
- Be honest and transparent about your experience and skills, and don't exaggerate your abilities or claim to have expertise you don't possess.
- Research the company culture and values, and be prepared to discuss how your own values and work style align with those of the company.
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