Company Name: Select Minds LLC

Job Details: $60-$75/hrRemoteFull,Time

Job Url: https://hiring.cafe/viewjob/15mdboravytb3ybg

Job Description: Posted 2mo agoSenior AI / ML Engineer@ Select Minds LLCView All JobsWebsiteDallas, Texas, United States$60-$75/hrRemoteFull TimeResponsibilities:lead design, build pipelines, deploy modelsRequirements Summary:5+ years AI/ML engineering, including 3+ years in MLOps; strong AWS SageMaker, Databricks, and CI/CD; Python; production ML deployment; Docker/Kubernetes; big data; cloud platforms.Technical Tools Mentioned:AWS SageMaker, Databricks, Python, R, SAS, Docker, Kubernetes, REST APIs, JSON, Spark, Hadoop, ETL, AWS, Azure, GCP, CI/CD
Benefits:
  
      Health insurance
      Opportunity for advancement
      Vision insurance
  


  
Senior AI / ML Engineer Dallas, Tx - Remote7+ Years (3+ Years in MLOps)Roles and Responsibilities	- 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 operationalizationRequired Qualifications	- 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 skillsPreferred Qualifications	- Hands-on experience building or integrating Generative AI solutions	- Background in software engineering and data analytics	- Strong problem-solving skills and ability to drive technical decision-making

Work remote temporarily due to COVID-19.