Lead Machine Learning Engineer (United States)

New York City, United States

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Bjak

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About Us

Bjak is focused on providing access to affordable and sustainable financial services for people in ASEAN. Headquartered in Malaysia, Bjak is the largest insurance portal in Southeast Asia. Our main portal, Bjak.com, helps millions find the insurance policy with the best value and highest coverage for them. Our investments in technology such as Custom API, trading systems and data science is to enable easy access to financial services that were previously inaccessible or difficult to understand.

Join us on this exciting journey as we expand our operations in United States. We're looking for dynamic individuals who share our vision and want to contribute to the next chapter of Bjak's success.

Job Description:

We are seeking a talented and experienced Lead Machine Learning Engineer to lead our machine learning efforts. As the Lead Machine Learning Engineer, you will play a key role in driving the development and implementation of machine learning models and solutions to solve complex problems and drive innovation across our organization.

Responsibilities:

  • Lead and mentor a team of machine learning engineers, providing technical guidance, mentorship, and support.
  • Collaborate with cross-functional teams to understand business requirements and translate them into machine learning solutions.
  • Design, develop, and deploy machine learning models and algorithms to address a variety of business challenges and opportunities.
  • Conduct exploratory data analysis, feature engineering, and model evaluation to prepare data and assess model performance.
  • Optimize machine learning models for scalability, reliability, and performance in production environments.
  • Develop and maintain data pipelines and workflows for efficient data processing and model training.
  • Stay updated on the latest advancements in machine learning technologies, tools, and frameworks.
  • Participate in code reviews, architectural discussions, and technical documentation efforts.
  • Collaborate with product managers and stakeholders to prioritize and roadmap machine learning initiatives.
  • Lead and contribute to research projects and experiments to explore new machine learning techniques and applications.

Requirements

 

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field.
  • 3 - 5 years of experience in machine learning development, with a focus on leading projects or teams.
  • Proficiency in programming languages such as Python, R, or Java.
  • Strong understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, reinforcement learning, etc.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
  • Knowledge of data processing and analysis tools such as pandas, NumPy, Spark, etc.
  • Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud Platform) for machine learning development and deployment.
  • Excellent problem-solving and analytical skills, with a focus on delivering high-quality solutions.
  • Strong leadership, communication, and collaboration abilities.
  • Ability to adapt to changing priorities and work effectively in a fast-paced environment.

 

Benefits

  • Fast moving, challenging and unique business problems
  • Strong learning and development plans for your career growth
  • International work environment and flat organization
  • Competitive salary
  • Flexible working hours & arrangement, Casual work attire

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: APIs AWS Azure Computer Science Data analysis Data pipelines Deep Learning EDA Engineering Feature engineering GCP Google Cloud Java Machine Learning Mathematics ML models Model training NumPy Pandas Pipelines Python PyTorch R Reinforcement Learning Research Scikit-learn Spark TensorFlow Unsupervised Learning

Perks/benefits: Career development Competitive pay Flex hours

Region: North America
Country: United States
Job stats:  8  1  0

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