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ML Engineer - job 1 of 2

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This role is for one of the Weekday's clients

We are looking for a Machine Learning Engineer to design, develop, and deploy ML models and pipelines that drive impactful business solutions. In this role, you will collaborate with cross-functional teams to build intelligent systems that enhance decision-making and automation.

Key Responsibilities:

Develop, train, and deploy machine learning models to solve real-world challenges.
Optimize models for performance, scalability, and accuracy.
Build and maintain ML pipelines for data preprocessing, training, and inference.
Work closely with data scientists, engineers, and product teams to identify AI-driven solutions.
Continuously monitor, fine-tune, and improve deployed models.
Stay up to date with the latest advancements in AI/ML technologies.

Required Skills & Experience:

Strong programming skills in Python, with experience in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Hands-on experience with data preprocessing, feature engineering, and model optimization.
Proficiency in building and deploying ML models on cloud platforms like AWS, GCP, or Azure.
Solid understanding of algorithms, statistics, and data structures.
Experience with MLOps tools for model versioning, deployment, and monitoring.
Strong problem-solving skills and keen attention to detail.

Preferred Qualifications:

Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
Experience working with big data technologies like Spark or Hadoop.
Knowledge of NLP, computer vision, or reinforcement learning.

Average salary estimate

$100000 / YEARLY (est.)

min

max

$80000K

$120000K

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What You Should Know About ML Engineer, Weekday

We are excited to introduce an incredible opportunity for a passionate Machine Learning Engineer to join one of Weekday's esteemed clients. In this dynamic role, you will be at the forefront of designing, developing, and deploying machine learning models and pipelines that create significant business impact. Working in collaboration with cross-functional teams, you will contribute to building intelligent systems that enhance decision-making processes and automation workflows. As a Machine Learning Engineer, your key responsibilities include developing, training, and deploying robust machine learning models to tackle real-world challenges. You will also be optimizing models to ensure performance, scalability, and accuracy, while building and maintaining ML pipelines that cover everything from data preprocessing and model training to inference. Close collaboration with data scientists, engineers, and product teams is essential to identify and implement AI-driven solutions that meet the needs of the business. You'll continuously monitor and fine-tune your deployed models to ensure they deliver the best outcomes, all while staying updated with the latest advancements in AI and ML technologies. Strong programming skills in Python and experience with ML frameworks like TensorFlow and PyTorch are must-haves, along with hands-on experience in data preprocessing and model optimization. Familiarity with cloud platforms for deployment and a solid grasp of algorithms and data structures will also be critical to your success. If you have a background in Computer Science, AI, or Data Science, and you're eager to push the boundaries of what's possible with machine learning, this role could be your perfect fit!

Frequently Asked Questions (FAQs) for ML Engineer Role at Weekday

What are the main responsibilities of a Machine Learning Engineer at Weekday?

As a Machine Learning Engineer at Weekday's client, your main responsibilities will include developing, training, and deploying machine learning models that address real-world challenges. You'll optimize these models for performance and scalability, build and maintain ML pipelines, and collaborate closely with data scientists and engineers to identify AI-driven solutions that enhance business processes.