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Associate Machine Learning Engineer (Remote)

Remote (USA)

About the Role

We are seeking a talented and motivated Machine Learning Engineer I to join our growing team. This is an exciting opportunity for an early-career professional who is passionate about building machine learning solutions that create meaningful user experiences at scale.

The ideal candidate enjoys solving complex problems, writing production-quality code, and collaborating with cross-functional teams to develop and deploy intelligent systems. You will work closely with data scientists, software engineers, and product teams to build and optimize machine learning models that drive business impact.

Key ResponsibilitiesDevelop, train, and deploy machine learning models for personalization, recommendations, and customer-focused applications.Build scalable data pipelines for feature engineering, model training, evaluation, and inference.Collaborate with data scientists and software engineers to transition research and prototypes into production systems.Improve recommendation and ranking models using large-scale behavioral and engagement data.Monitor and evaluate model performance through experimentation, A/B testing, and data-driven analysis.Write clean, maintainable, and efficient Python code following software engineering best practices.Support initiatives that enhance customer engagement and business outcomes through machine learning solutions.Required QualificationsBachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative field.1-3 years of relevant experience, including internships, research, academic projects, or professional experience.Strong programming skills in Python.Solid understanding of machine learning fundamentals, including:Supervised learningClassification and regressionFeature engineeringModel evaluation and validationExperience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.Experience working with SQL and large datasets.Familiarity with Git and software development best practices.Strong analytical and problem-solving skills.Why Join Us?Work on machine learning products that impact large-scale user experiences.Collaborate with highly skilled engineers, data scientists, and researchers.Gain hands-on experience deploying production-grade machine learning solutions.Grow your expertise in modern ML technologies and scalable systems.Flexible remote work environment with opportunities for learning and career development.

GCS is acting as an Employment Business in relation to this vacancy.

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We're looking for DOCSIS Engineer and you'll review the platform's RF-plant analysis and confirm it reflects what is genuinely happening on a live DOCSIS network. You'll be the human authority that tells the client "yes, this is right" or "here's where it's off, and here's what it's missing."

What you'll be doing

Reviewing automated RF-plant analysis and validating it against what is actually happening on the network - confirming the platform isn't misreading or over-stating the data.Sanity-checking the interpretation of RF performance, signal behavior, and physical-layer impairments across the plant.Assessing the platform's predictive trending - whether its "this is starting to degrade" calls hold up against real-world DOCSIS RF expertise.Delivering a clear, expert read on what's solid, what's inaccurate, and what additional signals should be considered.

What we're looking for

Deep, hands-on DOCSIS RF / HFC physical-layer expertise- gained at a cable operator (MSO) or equipment vendor.Strong ability to read RF plant performance- spectrum behavior, signal levels, noise and impairments - not just protocol or IP-layer data.Practical live-plant diagnostic experience- sweep/balance, signal forensics, and proactive network maintenance (PNM)-style analysis.Solid DOCSIS 3.1 and 3.0 knowledge.Comfort reviewing and critiquing analytic output- forming and clearly communicating an expert verdict.

GCS is acting as an Employment Business in relation to this vacancy.

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We're looking for DOCSIS Engineer and you'll review the platform's RF-plant analysis and confirm it reflects what is genuinely happening on a live DOCSIS network. You'll be the human authority that tells the client "yes, this is right" or "here's where it's off, and here's what it's missing."

What you'll be doing

Reviewing automated RF-plant analysis and validating it against what is actually happening on the network - confirming the platform isn't misreading or over-stating the data.Sanity-checking the interpretation of RF performance, signal behavior, and physical-layer impairments across the plant.Assessing the platform's predictive trending - whether its "this is starting to degrade" calls hold up against real-world DOCSIS RF expertise.Delivering a clear, expert read on what's solid, what's inaccurate, and what additional signals should be considered.

What we're looking for

Deep, hands-on DOCSIS RF / HFC physical-layer expertise- gained at a cable operator (MSO) or equipment vendor.Strong ability to read RF plant performance- spectrum behavior, signal levels, noise and impairments - not just protocol or IP-layer data.Practical live-plant diagnostic experience- sweep/balance, signal forensics, and proactive network maintenance (PNM)-style analysis.Solid DOCSIS 3.1 and 3.0 knowledge.Comfort reviewing and critiquing analytic output- forming and clearly communicating an expert verdict.

GCS is acting as an Employment Business in relation to this vacancy.

Read less