> Markdown version of [/jobs/ext/1881055-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/1881055-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** AllSTEM Connections - **Location:** Ontario, CA, United States - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Algorithm Design, Amazon Web Services, Artificial Neural Networks, Automation of Tests, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Continuous Delivery, Continuous Integration, Data Integration, DevOps, R (Programming Language), Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Software Deployment, Software Engineering, SQL Databases, Freeform SQL, Google Cloud, Pytorch, Delivery Pipeline, Deep Learning, Keras, Machine Learning Operations, Text Analysis, Unsupervised Learning - **Published:** August 1, 2026 - **Apply:** https://www.dice.com/job-detail/3fdc23f0-f9dc-49a8-b597-6a8e1c5d8125 ## About the Role We are seeking an experienced and driven Machine Learning Engineer to design, build, and optimize scalable machine learning models that drive intelligent applications. In this role, you will develop advanced algorithms, implement natural language processing (NLP) solutions, and streamline the end-to-end model lifecycle from research to production., Experience Baseline: Professional experience designing, deploying, and maintaining machine learning models in production environments. Technical Mastery: oDeep theoretical and practical knowledge of supervised and unsupervised learning algorithms. oProven experience building neural networks and natural language processing (NLP) applications. oStrong programming proficiency in Python, R, and SQL. oHands-on experience with core ML frameworks: TensorFlow, Keras, and PyTorch. Core Competencies: Working knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform) and practical implementation of DevOps/MLOps pipelines for model serving and monitoring. Preferred Attributes Experience optimizing model inference latency and resource utilization in cloud-native environments. Strong collaboration and communication skills, with the ability to bridge data science research and software engineering production standards. ## Description This is a hands-on technical role where you will leverage your expertise in supervised/unsupervised learning, neural networks, and modern ML frameworks. Working closely with data science and engineering teams, you will utilize cloud platforms, implement robust MLOps and DevOps practices, and ensure high-performance model deployment and management. If you are passionate about turning complex data into production-ready AI solutions, we want to hear from you., Model Development & Architecture Algorithm Design: Develop, train, and optimize supervised and unsupervised learning algorithms to solve complex business challenges. Neural Networks & NLP: Design and implement deep learning architectures and natural language processing (NLP) pipelines for text analysis and intelligent automation. Data Integration: Utilize Python, R, and advanced SQL queries to extract, clean, and manipulate large datasets for model training and evaluation. MLOps & Production Deployment Framework Implementation: Build and fine-tune models using industry-standard machine learning frameworks such as TensorFlow, Keras, and PyTorch. Pipeline Automation: Implement robust DevOps and MLOps practices, managing model registries, automated testing, continuous integration/continuous delivery (CI/CD) for ML, and model monitoring in production. Cloud Infrastructure: Deploy and scale machine learning workloads across cloud platforms and technologies, ensuring cost-efficiency, security, and low-latency inference., AllSTEM Connections participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program. _Participation_Poster_ES.pdf We also consider for employment qualified applicants regardless of criminal histories, consistent with legal requirements, including, if applicable, the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. Pursuant to applicable state and municipal Fair Chance Laws and Ordinances, we will consider for employment-qualified applicants with arrest and conviction records, including, if applicable, the San Francisco Fair Chance Ordinance. For Los Angeles, CA applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. ## Related Videos - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)