Machine learning Engineer

Adidev Technologies•California City, CA

17h

About The Position

Adidev Technologies is seeking a Machine Learning Engineer to deploy and refine machine learning models, particularly Generative AI, and turn ideas into AI-driven features and services for client projects. The role covers the full lifecycle of data modeling, from understanding business requirements and analyzing data to developing, deploying, and monitoring models. The engineer will collaborate across functions to integrate Generative AI into products, apply current ML research and practices, and support ethical, compliant AI implementations. Adidev Technologies is an IT consulting firm serving major companies and startups. The company describes support for employees through development guidance, subject-matter experts, project placement, and opportunities to gain industry experience.

Requirements

Degree in Computer Science, Engineering, Statistics, or a related technical field.
Demonstrable experience in machine learning, deep learning, NLP, computer vision, reinforcement learning, or other AI domains.
Demonstrable industry experience with Generative AI models and frameworks, such as GANs or Transformers.
Practical experience with SQL or NoSQL databases, data visualization tools, and version control systems.
Strong understanding of algorithmic complexity and data structure optimization.
Excellent problem-solving, collaboration, and communication abilities.
Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, and scikit-learn.
Strong background in cloud computing and big data platforms such as AWS, Azure, or GCP, including hands-on experience with cloud-based ML services and serverless architectures.
Familiarity with DevOps for AI, including Docker, Kubernetes, CI/CD pipelines, and MLOps practices.
Must be a US citizen, Green Card holder, or GC-EAD holder; visa sponsorship is not available.

Responsibilities

Architect and refine machine learning models and algorithms, translating complex datasets into actionable solutions.
Manage the data-modeling lifecycle, from understanding business requirements through deployment and monitoring.
Perform data analysis, preprocessing, feature engineering, and algorithm optimization.
Use Generative AI methods to develop novel solutions and applications, including text generation and image synthesis.
Collaborate across functions to integrate Generative AI models into offerings and improve product capabilities and user experiences.
Analyze large datasets to identify trends, anomalies, and opportunities for improvement.
Conduct exploratory data analysis and use insights to inform strategic decisions.
Keep current with machine learning developments and implement relevant tools and practices, including AutoML, MLOps, and interpretability frameworks.
Apply current AI research, especially in Generative AI, to project innovation.
Promote compliance with industry standards, regulatory requirements, ethical guidelines, and data privacy standards.
Facilitate team knowledge sharing and best practices in AI and machine learning, particularly Generative AI.