About Command|Link

Command|Link is a global SaaS Platform providing network, voice services, and IT security solutions, helping corporations consolidate their core infrastructure into a single vendor and layering on a proprietary single pane of glass platform. Command|Link has revolutionized the IT industry by tackling the problems our competitors create. In recognition for our unprecedented innovation and dedication, Command|Link was recognized as the SD-WAN Product of the Year, ITSM Visionary Spotlight, UCaaS Product of the Year, NaaS Product of the Year, Supplier of the Year, and the AT&T Strategic Growth Partner. Command|Link has built the only IT platform for scale that solves ISP vendor sprawl and IT headaches. We make it easy for our customers to get more done, maximize uptime and improve the bottom line.

Learn more about us here!

This is a 100% remote position

About your new role:

 
We are seeking a highly skilled Data Scientist with a strong focus on machine learning model development and deployment. In this role, you will design, build, and operationalize predictive models that drive business impact across our platform. You’ll work closely with engineering, product, and business teams to turn complex data into scalable, production-ready solutions. 

Key Responsibilities:

• Design, develop, and validate machine learning models for classification, regression, recommendation, NLP, or time-series use cases. 
• Own the full ML lifecycle: data exploration, feature engineering, model selection, training, testing, deployment, and monitoring. 
• Collaborate with data engineering teams to ensure data pipelines are optimized for modeling and production use. 
• Deploy ML models into production environments, ensuring scalability, reliability, and low-latency performance. 
• Monitor and maintain deployed models, performing re-training and tuning as needed to ensure continued accuracy and relevance. 
• Work with product managers and stakeholders to translate business requirements into measurable ML solutions. 
• Research and experiment with emerging ML algorithms, frameworks, and deployment strategies. 

What you'll need for success:

• 3+ years of professional experience as a Data Scientist or ML Engineer. 
• Proven experience building and deploying machine learning models in production environments. 
• Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). 
• Strong knowledge of model deployment frameworks and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, or equivalent). 
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) for ML workflows. 
• Solid understanding of data structures, algorithms, and applied statistics. 
• Strong problem-solving skills and the ability to communicate complex ideas clearly to both technical and non-technical audiences. 
• Advanced degree (MS or PhD) in Computer Science, Data Science, Statistics, Operations Research or related field. 

Nice to Have 

• Experience with MLOps best practices (CI/CD pipelines for ML, monitoring, and governance). 
• Exposure to big data technologies (Spark, Databricks, Kafka). 
• Background in deep learning, NLP, or computer vision applications. 

Why you'll love life at Command|Link

Join us at CommandLink, where you'll have the opportunity to shape the future of business communication. We value the innovative spirit and seek individuals ready to bring their unique vision and expertise to a team that values bold ideas and strategic thinking. Are you ready to make an impact?

• Room to grow at a high-growth company
• An environment that celebrates ideas and innovation
• Your work will have a tangible impact
• Generous Medical, Dental, and Vision coverage for full-time employees
• Flexible time off  
• 401k to help you save for the future
• Fun events at cool locations
• Free DoorDash lunches on Fridays
• Employee referral bonuses to encourage the addition of great new people to the team

Commandlink hires individuals in a number of geographic regions and the pay ranges listed reflect the cost of labor across these regions. The base pay for this position as displayed at the bottom of the job description is a range based on our lowest geographic region, up to our highest geographic region. Pay is based on location among other factors, such as skill-set, experience, and qualifications held.