Senior Machine Learning Engineer

3 weeks ago

delhi, India ELife Full time
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. All employees outside San Francisco headquarter work remotely.
Elife is a Startup developing innovative technology in the passenger transport industry, providing any type of ground transportation worldwide, including Group/event transportation, NEMT transportation, senior and disability transportation, pet relocation, bilingual driver for non-English speak clients.
Our market is the world. Our customers are everywhere. Our platform and apps are built on the cloud. We have endless exciting problems to solve, and we only use the best and latest technology.
Vacancy: Sr Machine Learning Engineer
Job description
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
Bachelor's or master's degree in computer science, mathematics, statistics, or related field.
Proficient in Python, SQL, and other relevant programming languages.
Strong background in machine learning, natural language processing, artificial intelligence, predictive modeling, statistical modeling.
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.
5+ years of experience.
Qualifications:
Expertise in Python or Java with and 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, Cloud Formation, EKS, AWS Security and Networking).
Experience with distributed large-scale data processing
Basic understanding of Machine Learning projects lifecycle.
Experience building and scaling machine learning models using large amounts of data
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
Experience in developing deep learning-based models and working on LLM-related applications
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

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