Job summary
Job post source
This job is from a recruiting firm hiring for a separate company because Worky is described as a talent cloud platform connecting companies with remote professionals, indicating it acts as an intermediary rather than the direct employer.
Job overview
The Senior Machine Learning Engineer role involves developing and deploying scalable machine learning models to drive innovative solutions within client projects facilitated by Worky.
Responsibilities and impact
The candidate will design, develop, and deploy machine learning models, collaborate with cross-functional teams to integrate models into production, perform data preprocessing and feature engineering, stay updated on ML advancements, and participate in the full software development lifecycle.
Experience and skills
The role requires 5+ years of experience with Python and ML libraries like TensorFlow, PyTorch, or scikit-learn, expertise in data preprocessing, feature engineering, cloud deployment, and version control, with preferred skills including deep learning, big data technologies, MLOps, NLP, computer vision, Agile methodologies, and backend technologies.
Company information
Worky is a global on-demand talent cloud platform specializing in connecting companies with vetted remote professionals in data, software engineering, and product development, emphasizing quality, technology integration, and personalized talent acquisition.
Job location and travel
The position supports remote work as Worky connects companies with remote professionals globally.
Company overview
Worky is a technology company focused on providing innovative solutions for remote work and productivity. They primarily generate revenue through their software-as-a-service (SaaS) platform, which offers tools for virtual collaboration, project management, and communication. Founded in 2019, Worky has quickly gained traction by addressing the growing demand for flexible work environments and has been recognized for its user-friendly interface and robust feature set. The company's mission is to empower teams to work efficiently from anywhere, and they continue to expand their offerings to meet the evolving needs of the modern workforce.
How to land this job
Tailor your resume to emphasize your extensive experience in developing and deploying machine learning models, highlighting proficiency with Python and libraries like TensorFlow, PyTorch, or scikit-learn as these are crucial for the Senior Machine Learning Engineer role at Worky.
Showcase your skills in data preprocessing, feature engineering, model evaluation, and cloud platform deployment (AWS, Google Cloud, Azure) to align with the job's core responsibilities and must-have skills.
Apply through multiple channels such as Worky's official corporate website and LinkedIn to maximize your chances of being noticed for this position.
Connect with current Worky employees in the machine learning or data science divisions on LinkedIn; use ice breakers like commenting on recent AI projects they've shared or asking about their experience integrating ML models at Worky to build rapport.
Optimize your resume for ATS by including keywords from the job description such as 'machine learning models,' 'Python,' 'TensorFlow,' 'cloud deployment,' and 'feature engineering' to ensure it passes initial automated screenings.
Leverage Jennie Johnson's Power Apply feature to automate tailored applications across platforms, identify relevant LinkedIn contacts for networking, and optimize your resume for ATS, allowing you to focus on preparing for interviews and skill enhancement.
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