Senior Machine Learning Engineer

Our Company:

A fast-growing start-up headquartered in San Francisco, CA, USA in the heart of Silicon Valley. We recruit worldwide as our customer base is global. Reliable ground transportation provider, any type of vehicle globally.

Vision:

Mission:

Corporate Culture: team first

• Partner-centric
• Team collaboration,
• Never "not my job", end-to-end ownership,
• Continuous learning and improvement,
• Hard-working and pragmatic,
• Don’t be a middleman,
• Result-driven

Job title: Sr Machine Learning Engineer

• Develop and implement machine learning models using Python, SQL, and other relevant tools.
• Collaborate with cross-functional teams to identify opportunities for applying machine learning techniques to business problems.
• Conduct research and experimentation to explore new machine learning approaches and technologies.
• Optimize existing machine learning models for improved performance and efficiency.
• Provide technical leadership and mentorship to junior members of the team.

Job requirements

• Strong background in machine learning, natural language processing, artificial intelligence, predictive modeling, statistical modeling.
• In-depth knowledge of reinforcement learning algorithms (e.g., DQN, PPO, Actor-Critic) with hands-on project experience.
• Proven experience in time series forecasting methods (e.g., ARIMA, LSTM, Prophet) and their practical application
• Proficient in Python, SQL, and other relevant programming languages.
• Familiarity with cloud computing platforms such as AWS or Azure is a plus.
• Ability to work collaboratively in a dynamic environment and communicate effectively with stakeholders at all levels of the organization.
• Bachelor’s or master’s degree in computer science, mathematics, statistics, or related field with a minimum of 5 years of experience

Qualifications:

• Expertise in Python with the ability to write performant production-quality code, familiarity with SQL.
• Experience building and operating large-scale distributed systems using Amazon Web Services (S3, Kinesis, CloudFormation, EKS, AWS Security and Networking).
• Experience with distributed large-scale data processing
• Basic understanding of the machine Learning project lifecycle.
• Experience building and scaling machine learning models using large amounts of data
• Expertise in Python and the ability to write performant production-quality code, familiarity with SQL.

It’s great, but not required, if you have

• Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
• Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions