Senior ML Engineer — Generative AI & Deployment Leader

Adidev Technologies Inc; New York (NY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive salary range

Relocation assistance

Remote support

Job summary

Adidev Technologies Inc. seeks a Mid‑ Senior Machine Learning Engineer to lead deployment of advanced ML models with a focus on Generative AI in a US-based team. You will shape AI-driven solutions from ideation through production, working across data science, software and client-facing projects.

The role emphasizes Generative AI experiments, model optimization, and scalable data pipelines on cloud platforms. Strong Python and ML library expertise, plus DevOps for AI, are required for success.

Qualifications

• Degree in Computer Science, Engineering, Statistics, or a related technical field.
• Demonstrable experience in machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI domains.
• Demonstrable experience with Generative AI models and frameworks, such as GANs or Transformers, applied in industry settings.
• Practical experience with SQL/NoSQL databases, data visualization tools, and version control systems.
• Strong foundational understanding of algorithmic complexity and data structure optimization.
• Excellent problem-solving, collaboration, and communication abilities.
• Develop and implement cutting‑edge machine learning models, with a particular focus on Generative AI applications such as text generation, image synthesis, and creative AI.
• Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.
• Stay ahead of AI research, especially in Generative AI, applying the latest findings and techniques to drive innovation within our projects.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit‑learn).
• Strong background in cloud computing and big data platforms (AWS, Azure, GCP), with hands‑on experience in cloud‑based ML services and serverless architectures.
• Familiarity with DevOps for AI, including containerization (Docker, Kubernetes), CI/CD pipelines, and MLOps practices.
• Facilitate knowledge sharing and best practices in AI/ML, particularly focusing on Generative AI, within the team.
• Ensure all AI implementations are compliant with ethical guidelines and data privacy standards.

Responsibilities

• Architect and refine sophisticated ML models and algorithms, translating complex datasets into actionable solutions.
• Engage in the full lifecycle of data modeling projects, from understanding business requirements to deployment and monitoring.
• Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.
• Lead cross-functional collaborations to integrate Generative AI models into our offerings, enhancing product capabilities and user experiences.
• Apply advanced analytical techniques to analyze vast datasets, identifying trends, anomalies, and opportunities for improvement.
• Execute data preprocessing, feature engineering, and algorithm optimization to enhance model accuracy and efficiency.
• Conduct exploratory data analysis to extract valuable insights and influence strategic decisions.
• Keep abreast of and implement the latest ML trends, tools, and best practices, including AutoML, MLOps, and interpretability frameworks.
• Promote compliance with industry standards and regulatory requirements, emphasizing ethical AI practices.

Skills

Generative AI

Machine Learning

Deep Learning

NLP

Computer Vision

Reinforcement Learning

Python

TensorFlow

PyTorch

SQL

NoSQL

Cloud (AWS/Azure/GCP)

DevOps for AI

MLOps

Education

Bachelor's/Master's in CS/EE/Stats

Tools

Docker

Kubernetes

Git

CI/CD

MLOps

AWS

Azure

GCP

Job description

Adidev Technologies Inc. seeks a Mid‑ Senior Machine Learning Engineer to lead deployment of advanced ML models with a focus on Generative AI in a US-based team. You will shape AI-driven solutions from ideation through production, working across data science, software and client-facing projects.

The role emphasizes Generative AI experiments, model optimization, and scalable data pipelines on cloud platforms. Strong Python and ML library expertise, plus DevOps for AI, are required for success.