Senior AI / ML Engineer

Job not on LinkedIn

November 27

🤠 Texas – Remote

Although this job is listed in Texas, this company may be open to hiring remote in other states.

💵 $60 - $75 / hour

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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Select Minds LLC

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SaaS • Enterprise • B2B

Select Minds LLC is a digital transformation company that specializes in providing comprehensive IT solutions, including application development, enterprise UX, infrastructure management, and analytics. With a focus on tailored digital communication and innovative solutions, Select Minds empowers organizations to enhance their digital capabilities and achieve business success. The company emphasizes its commitment to collaboration and adaptability, ensuring that clients receive customized services that meet their unique needs for today's and tomorrow's challenges.

51 - 200 employees

Founded 2017

☁️ SaaS

🏢 Enterprise

🤝 B2B

📋 Description

• Lead the design and development of AI and ML applications across cloud or on-prem environments • Build, maintain, and optimize MLOps pipelines for model training, deployment, monitoring, and retraining • Integrate Generative AI models into enterprise applications and workflows • Apply deep learning, neural networks, image processing, or conversational AI where needed • Act as the SME for AI/ML engineering practices, standards, and solution architecture • Collaborate with cross-functional teams to support end-to-end delivery • Ensure production systems meet reliability, scalability, and performance standards • Guide and mentor junior engineers and contribute to technical leadership • Support data engineering pipelines, data preparation, and model operationalization

🎯 Requirements

• 5+ years of experience in AI/ML engineering, including 3+ years in MLOps • Strong hands-on experience with AWS SageMaker, Databricks, and CI/CD tools • Proficiency in Python; experience with R or SAS is an advantage • Experience deploying, monitoring, and optimizing ML models in production environments • Knowledge of Docker, Kubernetes, REST APIs, and JSON processing • Familiarity with big-data ecosystems such as Spark or Hadoop • Solid understanding of ETL processes, data modeling, and data engineering practices • Experience with cloud platforms (AWS, Azure, or GCP) and ML-focused architectures • Strong version control, dependency management, and automation skills

🏖️ Benefits

• Health insurance • Opportunity for advancement • Vision insurance