Enormous Enterprise LLC
Alpharetta, Georgia
Machine Learning Engineer Remote Role : Alpharetta Georgia 30009 W2 Candidates : with minimum validity of 12 months Must have: Need good clinical and claims knowledge 7+ years of healthcare exp 4+ years of experience in machine learning, NLP, or deep learning They are working on AI evidence engine focused on LLM 2 rounds of Zoom interview then offer. What Youll Do Develop, fine-tune, and optimize LLMs and modern deep learning models Write high-quality prompts, instructions, and training examples to shape model behavior Design, implement, and maintain instruction orchestration and evaluation workflows for LLM-based systems Build and maintain training pipelines, datasets, and evaluation workflows Design and execute functional and automated tests to validate AI outputs and system behavior Analyze model performance, identify failure patterns (e.g., accuracy gaps, hallucinations, edge cases), and drive improvements Collaborate with engineering and product teams (and review partner or vendor work) to deploy and iterate on AI features Contribute to the ongoing maintenance and improvement of existing AI systems What Were Looking For 7+ years of experience in machine learning, NLP, or deep learning Hands-on experience with LLMs (GPT, LLaMA, Mistral, or similar) in applied or production contexts Healthcare data experience is required, including working knowledge of: Strong Python skills; experience with PyTorch or TensorFlow Familiarity with HuggingFace tools and modern model-training workflows Experience evaluating AI output quality, hallucination behavior, reliability, and consistency Experience designing automated evaluation, regression testing, or benchmarking pipelines for AI systems Ability to work with minimal direction, take ownership of problem areas, and operate effectively in ambiguous problem spaces Excellent communication skills for writing prompts, instructions, technical documentation, and evaluation artifacts Experience optimizing LLM and deep learning workloads on AWS, including model training, GPU utilization, and cost-efficient inference deployments
Machine Learning Engineer Remote Role : Alpharetta Georgia 30009 W2 Candidates : with minimum validity of 12 months Must have: Need good clinical and claims knowledge 7+ years of healthcare exp 4+ years of experience in machine learning, NLP, or deep learning They are working on AI evidence engine focused on LLM 2 rounds of Zoom interview then offer. What Youll Do Develop, fine-tune, and optimize LLMs and modern deep learning models Write high-quality prompts, instructions, and training examples to shape model behavior Design, implement, and maintain instruction orchestration and evaluation workflows for LLM-based systems Build and maintain training pipelines, datasets, and evaluation workflows Design and execute functional and automated tests to validate AI outputs and system behavior Analyze model performance, identify failure patterns (e.g., accuracy gaps, hallucinations, edge cases), and drive improvements Collaborate with engineering and product teams (and review partner or vendor work) to deploy and iterate on AI features Contribute to the ongoing maintenance and improvement of existing AI systems What Were Looking For 7+ years of experience in machine learning, NLP, or deep learning Hands-on experience with LLMs (GPT, LLaMA, Mistral, or similar) in applied or production contexts Healthcare data experience is required, including working knowledge of: Strong Python skills; experience with PyTorch or TensorFlow Familiarity with HuggingFace tools and modern model-training workflows Experience evaluating AI output quality, hallucination behavior, reliability, and consistency Experience designing automated evaluation, regression testing, or benchmarking pipelines for AI systems Ability to work with minimal direction, take ownership of problem areas, and operate effectively in ambiguous problem spaces Excellent communication skills for writing prompts, instructions, technical documentation, and evaluation artifacts Experience optimizing LLM and deep learning workloads on AWS, including model training, GPU utilization, and cost-efficient inference deployments
Jobot
Los Angeles, California
W2 Machine Learning Engineer in Los Angeles, CA. Opportunity! This Jobot Consulting Job is hosted by: Robert Reyes Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume. Salary: $120,000 - $180,000 per year A bit about us: Prestige Hospital System Placed in both California in a broad assessment of excellence in hospital-based patient care. Why join us? Competitive Salary Stellar Benefits (Medical, Dental Vision, Life Insurance) Flexible Schedule Job Stability Career growth The position offers a competitive salary If you are passionate, thrive in a fast-paced environment and are ready to take your career to the next level, we would love to hear from you. Job Details Job Details: We are seeking a dynamic and innovative Consulting Machine Learning Engineer to join our Tech Services team. The successful candidate will be responsible for the full lifecycle management of machine learning models, including design, build, and maintenance. As an MLOps Engineer, you will play an integral role in implementing artificial intelligence solutions across our organization. You will partner with data scientists, data team members, and clinical operations to deploy, monitor, and maintain machine learning solutions that will improve operational efficiency and advance research. Responsibilities: Deploying and maintaining production-grade machine learning models, ensuring real-time inference, scalability, and reliability. Developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as AWS, GCP, or Azure. Leading engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks. Developing AI pipelines for various data processing needs, ensuring solutions meet all technical and business requirements. Collaborating with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines. Implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes. Setting up monitoring and logging solutions to track model performance, system health, and anomalies. Implementing version control systems for machine learning models and associated code. Ensuring machine learning systems meet security and compliance standards, including data protection and privacy regulations. Maintaining clear and comprehensive documentation of ML Ops processes and configurations. Qualifications: Bachelor's degree in computer science, artificial intelligence, informatics or closely related field. Master's degree in computer science, engineering or closely related field. Minimum of 3 years relevant Machine Learning Engineer Experience. Experience with AI and machine learning platforms (e.g., AWS, Azure or GCP). Proficiency in containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes). Experience with CI/CD tools (e.g., Github Actions). Proficiency in programming languages and frameworks (e.g., Python, R, SQL). Deep understanding of coding, architecture, and deployment processes. Strong understanding of critical performance metrics. Extensive experience in predictive modeling, LLMs, and NLP. Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems. Experience in managing end-to-end ML lifecycle and automation with Terraform is a must. Ability to effectively articulate the advantages and applications of the RAG framework with LLMs. Interested in hearing more? Easy Apply now by clicking the "Apply Now" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes, or other information you choose to submit is subject to Jobot's Privacy Policy, as well as the Jobot California Worker Privacy Notice and Jobot Notice Regarding Automated Employment Decision Tools which are available at By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here:
W2 Machine Learning Engineer in Los Angeles, CA. Opportunity! This Jobot Consulting Job is hosted by: Robert Reyes Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume. Salary: $120,000 - $180,000 per year A bit about us: Prestige Hospital System Placed in both California in a broad assessment of excellence in hospital-based patient care. Why join us? Competitive Salary Stellar Benefits (Medical, Dental Vision, Life Insurance) Flexible Schedule Job Stability Career growth The position offers a competitive salary If you are passionate, thrive in a fast-paced environment and are ready to take your career to the next level, we would love to hear from you. Job Details Job Details: We are seeking a dynamic and innovative Consulting Machine Learning Engineer to join our Tech Services team. The successful candidate will be responsible for the full lifecycle management of machine learning models, including design, build, and maintenance. As an MLOps Engineer, you will play an integral role in implementing artificial intelligence solutions across our organization. You will partner with data scientists, data team members, and clinical operations to deploy, monitor, and maintain machine learning solutions that will improve operational efficiency and advance research. Responsibilities: Deploying and maintaining production-grade machine learning models, ensuring real-time inference, scalability, and reliability. Developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as AWS, GCP, or Azure. Leading engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks. Developing AI pipelines for various data processing needs, ensuring solutions meet all technical and business requirements. Collaborating with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines. Implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes. Setting up monitoring and logging solutions to track model performance, system health, and anomalies. Implementing version control systems for machine learning models and associated code. Ensuring machine learning systems meet security and compliance standards, including data protection and privacy regulations. Maintaining clear and comprehensive documentation of ML Ops processes and configurations. Qualifications: Bachelor's degree in computer science, artificial intelligence, informatics or closely related field. Master's degree in computer science, engineering or closely related field. Minimum of 3 years relevant Machine Learning Engineer Experience. Experience with AI and machine learning platforms (e.g., AWS, Azure or GCP). Proficiency in containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes). Experience with CI/CD tools (e.g., Github Actions). Proficiency in programming languages and frameworks (e.g., Python, R, SQL). Deep understanding of coding, architecture, and deployment processes. Strong understanding of critical performance metrics. Extensive experience in predictive modeling, LLMs, and NLP. Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems. Experience in managing end-to-end ML lifecycle and automation with Terraform is a must. Ability to effectively articulate the advantages and applications of the RAG framework with LLMs. Interested in hearing more? Easy Apply now by clicking the "Apply Now" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes, or other information you choose to submit is subject to Jobot's Privacy Policy, as well as the Jobot California Worker Privacy Notice and Jobot Notice Regarding Automated Employment Decision Tools which are available at By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here: