Machine Learning Engineer (Contract)

Career.io

75d

About The Position

Career.io is seeking a highly experienced Machine Learning Engineer to join our innovative team. As a Machine Learning Engineer, you will be responsible for developing and implementing machine learning models and algorithms to solve complex business problems and drive data-driven decision-making. You will collaborate closely with data scientists, software engineers, and other stakeholders to deploy machine learning solutions in production environments.

Requirements

• ML experience with both classical ML and deep learning (PyTorch/TensorFlow).
• Proven track record shipping ML products end-to-end.
• Optimization and causal inference expertise including multi-objective optimization, constraint satisfaction, and counterfactual/scenario modeling.
• Familiarity with LLMs and generative AI.
• Strong software engineering fundamentals.
• Experience with data preprocessing, feature engineering, and data visualization.
• Understanding of supervised and unsupervised learning techniques.
• Familiarity with deep learning architectures and neural networks.
• Proficiency in using cloud platforms (e.g., AWS, Azure, GCP) for model deployment.
• Strong problem-solving skills.
• Excellent communication and teamwork skills.
• Experience with version control systems like Git.
• Knowledge of data privacy and security considerations in machine learning.
• Ability to work independently and adapt to fast-paced, evolving projects.

Nice To Haves

• Experience with reinforcement learning.
• Knowledge of containerization (e.g., Docker) and orchestration (e.g., Kubernetes).
• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Contributions to open-source machine learning projects or publications in the field.
• Experience with automated machine learning (AutoML) tools and platforms.

Responsibilities

• Develop and implement machine learning models and algorithms.
• Collaborate with data scientists, software engineers, and stakeholders.
• Deploy machine learning solutions in production environments.
• Handle messy real-world data and build scalable systems.
• Communicate technical concepts to non-technical stakeholders.

What This Job Offers