Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge large language model (LLM) and AI platform technologies to build scalable, secure, and production-ready AI systems. As we continue to grow, we’re looking for a skilled LLM Platform Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. We are looking for OPT/CPT/H4 EAD/TN/E3 or any other Non-immigrant visa people who are looking for an H1B sponsorship for the year 2027 quota. Company: Bright Vision Technologies ( www.bvteck.com ) Job Title: LLM Platform Engineer Onsite/Hybrid: Remote FULL-TIME ROLE WITH BRIGHT VISION Job Description: Environment: Large Language Models (LLMs), Python, Prompt Engineering, Model Fine-Tuning, Hugging Face, OpenAI / Azure OpenAI APIs, Vector Databases, Embeddings, RESTful APIs, Model Deployment & Scaling, Docker, Kubernetes, Cloud Platforms (AWS / Azure / GCP), CI/CD pipelines, Linux, Git, Agile methodologies BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE. For every role, a coding test is required, so apply only if you are confident and technically strong. We prefer at least 3 to 5 years real time experience. If you are an LLM Platform Engineer with the above skills and are looking for an H-1 B sponsorship this year, please send your resume immediately to harry@bvteck.com. we are committed to providing equal employment opportunities and fostering an inclusive work environment. We encourage applications from all qualified individuals regardless of race, ethnicity, religion, gender identity, sexual orientation, age, disability, or any other protected status. If you require accommodations during the recruitment process, please let us know. Position offered by “No Fee agency.” Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Responsibilities: • Develop machine learning models and algorithms to address business needs. • Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions. • Clean, preprocess, and analyze large datasets to extract meaningful insights. • Deploy machine learning models into production environments and monitor their performance. • Continuously improve model accuracy and performance through experimentation and optimization. • Stay up-to-date with the latest advancements in machine learning and related technologies. • Communicate findings and results to stakeholders in a clear and concise manner. Requirements: • Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field. • 2~5 years of experience in machine learning, data science, or a related field. • Proficiency in programming languages such as Python, Java, or Scala. • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. • Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. • Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform. • GCP Professional Machine Learning Engineer certification is required. • Experience with version control systems such as Git. • Excellent problem-solving skills and attention to detail. • Strong communication and collaboration skills. Preferred Qualifications: • Master's degree or higher in Computer Science, Engineering, Mathematics, or a related field. • Experience with distributed computing frameworks such as Apache Spark. • Familiarity with containerization and orchestration technologies such as Docker and Kubernetes. • Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. • Experience with natural language processing (NLP) or computer vision (CV) techniques. • Experience with continuous integration and continuous deployment (CI/CD) pipelines. • Contributions to open-source projects or participation in relevant communities.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role offers the opportunity to design, build, and deploy large-scale machine learning systems that drive personalized content discovery, search relevance, and intelligent ad optimization. The Senior Machine Learning Engineer will work across the full ML lifecycle, impacting millions of daily users. - Design, implement, and deploy production-grade ML models and systems at scale for content ranking, recommendation, and ad optimization. - Own the full ML lifecycle, including problem definition, feature engineering, training, evaluation, deployment, and monitoring. - Build scalable data and model pipelines with reliability, observability, and automated retraining. - Work with large-scale datasets to improve predictions, search relevance, and user/content understanding. - Research and apply advanced ML/AI techniques, including deep learning, graph-based models, transformers, and LLM evaluation. - Collaborate cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to deliver impactful ML solutions. - Contribute to technical strategy, architecture decisions, and the long-term ML roadmap. Qualifications - 3–5+ years of experience building, deploying, and operating machine learning systems in production. - Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals. - Proficiency in modern ML frameworks such as PyTorch or TensorFlow. - Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure. - Familiarity with recommender systems, search/ranking systems, advertising/auction systems, or large-scale representation learning. - Knowledge of distributed systems, big data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis), and low-latency real-time environments. - Experience with feature engineering, model optimization, and production monitoring. - Strong problem-solving skills and the ability to translate ambiguous business or product problems into ML solutions. - Preferred: experience with LLM/Generative AI techniques, advanced ML research, or prior work in large-scale user-facing platforms. Requirements - 3–5+ years of experience building, deploying, and operating machine learning systems in production. - Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals. - Proficiency in modern ML frameworks such as PyTorch or TensorFlow. - Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure. - Familiarity with recommender systems, search/ranking systems, advertising/auction systems, or large-scale representation learning. - Knowledge of distributed systems, big data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis), and low-latency real-time environments. - Experience with feature engineering, model optimization, and production monitoring. - Strong problem-solving skills and the ability to translate ambiguous business or product problems into ML solutions. - Preferred: experience with LLM/Generative AI techniques, advanced ML research, or prior work in large-scale user-facing platforms. Benefits - Competitive salary range of $185,800–$303,400 USD. - Equity opportunities through restricted stock units. - Comprehensive healthcare coverage including medical, dental, and vision. - 401(k) program with employer match. - Flexible vacation, paid volunteer time off, and generous parental leave. - Global benefit programs supporting professional development, caregiving, mental health, and family planning. - Remote-friendly, inclusive, and collaborative work environment.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Senior Machine Learning Engineer, you will own the end to end ML lifecycle at Button, from the data and feature pipelines that feed models, through training and evaluation workflows, to deployment, scoring, monitoring, and retraining. You will work closely with product managers, data scientists, and software engineers to translate ambiguous business problems into reliable production ML systems that integrate with our platform and power real product decisions. You will help build the infrastructure and patterns that allow models to move quickly from research to production while meeting real world requirements for latency, scalability, cost efficiency, reproducibility, and safety. This role works closely with our Data Teams and plays a central role in how machine learning powers Button’s commerce and monetization products. - Own the full ML lifecycle including feature pipelines, training workflows, model deployment, inference services, monitoring, and retraining. - Design and build reliable data and feature pipelines, including feature store patterns that support reproducible training and consistent features across training, batch scoring, and online inference. - Build and optimize machine learning models including regression, classification, ranking, and recommender systems. - Implement and manage batch scoring pipelines and online inference services with clear performance, reliability, and latency standards. - Partner with data scientists to operationalize models and build the tooling needed to run consistent evaluation, experimentation, and model iteration. - Collaborate with software engineers to ensure smooth integration of models into production services and APIs. - Establish observability for ML systems including monitoring of data freshness, feature drift, model performance, and pipeline health. - Design systems that support rapid experimentation and safe rollout of new models. - Document architecture clearly, establish best practices for ML engineering at Button, and mentor teammates through thoughtful code reviews and design discussions. - Contribute to the design of decisioning systems that power ranking, recommendations, and commerce optimization across Button’s platform. Qualifications - Write clear, maintainable code with strong software engineering practices including testing, documentation, debugging, and thoughtful system design. - Have experience building and operating production machine learning systems rather than only training models. - Understand the full ML lifecycle including feature generation, training pipelines, deployment strategies, and monitoring. - Have practical experience designing scalable data pipelines and feature generation workflows. - Have experience building or working with feature pipelines or feature stores that support both training and online inference. - Think deeply about reliability, scalability, latency, and cost efficiency when building ML systems. - Are comfortable working in cloud environments, especially AWS. Familiarity with Amazon SageMaker, Redis, Spark, streaming systems, or distributed data processing frameworks is a plus. - Have experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn. - Enjoy collaborating closely with engineers, data scientists, and product managers and can clearly communicate technical tradeoffs and design decisions. - Are comfortable working in ambiguous problem spaces and translating product questions into measurable ML solutions. Requirements - 5+ years of professional experience in machine learning engineering, software engineering, data engineering, or similar roles. - Fluency with Python and SQL. - Proven experience designing, building, and operating data pipelines at scale. - Hands on experience deploying and maintaining machine learning models in production environments. - Experience working in cloud environments, especially AWS. - Familiarity with orchestration and data modeling tools such as Airflow, dbt, or similar systems. - Experience building ranking, recommendation, or decisioning systems is a plus. Benefits - RemotePlus workplace, blending “work from anywhere” with in-person collaboration. - Salary range: $153,000 - $198,000. - 401(k) plan with 3% annual contribution from the company. - Unlimited time off (including birthdays off) and periodic Mental Health Weeks. - 100% premium coverage for health, vision, and dental insurance for employees; 75% for dependents. - Complimentary memberships to One Medical. - Monthly stipend for mobile phone/internet and an annual lifestyle stipend. - “All Access” memberships to WeWork in select markets and regular coworking days and social events.