Bright Vision Technologies is seeking a Machine Learning Engineer to develop, train, evaluate, and operationalize predictive and classification models for production applications.
Locations (2)
Frisco, Texas, United States
North Dallas, Texas, United States
Compensation
Salary Range: $115,000–$165,000 Annually
Responsibilities
Prepare datasets, engineer features, and build reproducible training and validation pipelines.
Develop, tune, and evaluate machine learning models for classification, regression, ranking, or forecasting use cases.
Implement model-serving components and integrate inference workflows with application and data platforms.
Track model performance, investigate drift or quality degradation, and recommend retraining or improvement actions.
Document experiments, model assumptions, evaluation results, and implementation decisions for engineering stakeholders.
As an AI Forward-Deployed Technical Manager, you will lead the delivery of cutting-edge AI and machine learning solutions for Advanced Semiconductor R&D Modules. You will own the relationship with internal engineering stakeholders from a technical delivery standpoint, translating complex semiconductor domain challenges into AI/ML roadmaps. You will manage a team of Forward-Deployed Engineers and Data Scientists to design, build, and deploy production-grade AI systems (including LLMs, RAG pipelines, and predictive models), ensuring measurable business impact, operational efficiency, and adherence to AI safety and data governance standards.
The Junior Machine Learning Engineer works within an Applied AI and Machine Learning delivery team to develop, test, deploy, and support AI and machine learning solutions. This early-career role is designed for candidates with strong programming and analytical foundations who want to build scalable, production-ready AI products under the guidance of senior engineers, data scientists, and technical leads.
Responsibilities
Assist in collecting, cleaning, transforming, profiling, and validating structured and unstructured data.
Perform exploratory data analysis to identify patterns, anomalies, trends, data quality issues, and potential features.
Develop and evaluate baseline machine learning models under guidance using appropriate algorithms and metrics.
Support use cases involving classification, regression, clustering, anomaly detection, forecasting, natural language processing, and Generative AI.
Write reusable, readable, secure, and testable Python code aligned with team coding standards.
Requirements
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, or a related area.
The Junior Machine Learning Engineer works within an Applied AI and Machine Learning delivery team to develop, test, deploy, and support AI and machine learning solutions. This early-career role is designed for candidates with strong programming and analytical foundations who want to build scalable, production-ready AI products under the guidance of senior engineers, data scientists, and technical leads.
Responsibilities
Assist in collecting, cleaning, transforming, profiling, and validating structured and unstructured data
Perform exploratory data analysis to identify patterns, anomalies, trends, data quality issues, and potential features
Develop and evaluate baseline machine learning models under guidance using appropriate algorithms and metrics
Support use cases involving classification, regression, clustering, anomaly detection, forecasting, natural language processing, and Generative AI
Write reusable, readable, secure, and testable Python code aligned with team coding standards
Internship focused on developing and supporting machine learning models within Bask Health's telehealth platform.
Responsibilities
Assist with developing machine learning models and supporting engineering systems across Bask Health
Work with experienced engineers to understand practical machine learning development workflows
Prepare, clean, and transform approved datasets for model training and evaluation
Write Python scripts for data processing, experimentation, and model development
Assist with implementing supervised learning models and baseline algorithms
Requirements
Currently pursuing, recently completed, or independently developing skills equivalent to a degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Software Engineering, Mathematics, Statistics, or a related technical field
Develops and programs integrated software algorithms to structure, analyze, and leverage structured and unstructured data in business and systems applications.
Compensation
The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level. – United States of America: Annual Salary USD 95,800 - 220,500 in Texas
Responsibilities
Design, develop, and implement AI and machine learning models, including data pre-processing, feature engineering, algorithm selection, training, and evaluation.
Build forecasting and predictive models for revenue, cost, and demand, and support scenario and "what-if" analysis for planning.
Gather, clean, and analyze large financial and operational datasets to train and test models, using statistical methods and visualization to surface insights.
Optimize models for performance through hyperparameter tuning, experimentation, and feature selection or dimensionality reduction.
Support GenAI and automation use cases (AI assistants, agents, workflow automation) across FP&A, cost accounting, and controllership.
Requirements
PhD in Mathematics, Applied Mathematics, Statistics, or a closely related quantitative field
Nice to have: GenAI/LLM tools
Nice to have: ERP/SAP data
Nice to have: interest in finance and business strategy
Develop machine learning models and data-driven capabilities that help Bask Health better understand patient experiences and improve how our platform supports patients throughout their telehealth journeys.
Responsibilities
Develop machine learning models that support patient experience and operational intelligence across Bask Health.
Analyze patient journey data to identify friction points, behavioral patterns, and opportunities for product improvement.
Build predictive models for approved patient engagement and workflow outcomes.
Develop models that help identify potential onboarding abandonment and incomplete workflows.
Analyze questionnaire completion patterns and other patient interaction signals.
Hands-on Applied Machine Learning Engineer with experience in Multimodal AI to work on the development and advancement of large-scale machine learning systems, focusing on designing, developing, experimenting with, and deploying ML models that analyze and classify diverse content across text, audio, and visual data.
Responsibilities
Design, develop, and improve machine learning models, particularly classification systems for large-scale applications.
Drive ML initiatives from research, ideation, and prototyping through experimentation, evaluation, and production deployment.
Develop and support Python-based data pipelines and workflows for ML model training, inference, and processing.
Build and evaluate multimodal machine learning solutions involving text, audio, and visual data.
Work with distributed computing and ML processing frameworks such as Ray to support scalable model development and execution.
Requirements
Bachelor's degree or relevant experience in a related field
Lead the end-to-end lifecycle of enterprise AI deployments—from initial scoping and proof-of-concept (PoC) to full production deployment and scaling.
Manage, mentor, and unblock a multidisciplinary team of AI/ML engineers, forward-deployed engineers, and data scientists embedded within engineering teams.
Translate complex domain problems into concrete data science and engineering requirements.
Bridge the gap between central IT/AI platforms and domain-specific R&D teams.
Ensure deployed AI models adhere to enterprise IP security, data privacy, and strict compliance standards.
Requirements
Master’s or PhD in Computer Science, Data Science, AI/ML, or a related quantitative engineering field.
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