$ 35,000 a 40,000
Tipo de puesto
Empleado de tiempo completo
Machine Learning Engineer
We are looking for a Machine Learning Engineer to join our team and be responsible for the quality, clarity and robustness of the machine learning pipeline
• Can you code proficiently in at least one
language used by data scientists and/or data engineers , and does it
excite you to learn more?
• Are you skilled at predictive modeling ?
• Do you view communication skills just as important as technical ones?
• Can you listen to the needs of your peers and customers and adapt where need be?
• Can you finish what you start?
• Can you own assignments given to you?
If the answer is "yes" to these questions, you could be an excellent fit to join our team
Responsibilities and Duties:
• Problem solve and assess technical problems, determine solutions, and work with internal engineering and customer teams to resolve them.
• Demonstrate ML solutions with engaging storytelling and technical accuracy.
• Architect, Design, and Deliver end to end machine learning workflows and systems from data ingestion to model deployment.
• Provide best practices and guidance to customers on machine learning workflows and systems from data ingestion to model deployment.
• Communicate effectively to a diverse audience including engineers and businesspeople
Bachelor's degree in engineering, computer science, mathematics or a related field. Graduate degree is a plus.
• 3+ years experience with performing hands on Data Science and Machine Learning, including their deployment in enterprise production systems.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• 3+ years experience using statistical computer languages (R, Python, Rust, etc.) to manipulate data and draw insights from large data sets.
• Deep expertise in Python and its data science libraries such as scikit-learn , pandas, NumPy, TensorFlow.
• Excellent oral and written English
• Large datasets and experience with big data processing tools like Spark, Kafka, Hadoop or Storm.
• Containerization (Docker, Kubernetes), microservices (Spring boot, event-driven) and non-relational stores (DynamoDB).
ML services (AWS) and extending them for our client use cases.
• Strong ability to juggle multiple priorities.
Strong bias for action and ownership.
• Profound know-how in software development incl. software testing, Continuous Integration, code reviews, etc.
• Previous startup experience would be a plus