Who We Are
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to Customers.
Job Description
Job Title : Senior Machine Learning (AI / ML ) Engineer - Azure
Job Type : W2 / C2C / 1099
Experience : 5-25 Years
Location : Fort Worth, Texas
Responsibilities
- 5 to 7 years of proven experience as a Machine Learning Engineer or in a similar role, with a strong track record of developing and deploying machine learning solutions in real-world applications within an Azure environment.
- Proficiency in programming languages such as Python, R, or Java.
- Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, sci-kit-learn), Azure ML, and Gen AI/LLMs.
- Solid understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing.
- Experience with data preprocessing, feature engineering, and dimensionality reduction techniques.
- Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
- Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
- Experience with Azure cloud platform and containerization technologies (e.g., Docker, Kubernetes) is a plus.
- Familiarity with version control systems (e.g., Git) and agile software development methodologies.
- Experience in deploying machine learning models in production environments using Azure.
- Knowledge of additional cloud platforms and container orchestration tools.
- Utilize programming languages such as Python, R, or Java, and relevant libraries and frameworks (e.g., TensorFlow, PyTorch, sci-kit-learn, Azure ML, Gen AI/LLMs).
- Optimize and maintain machine learning models to ensure high performance and scalability.
- Collaborate with data scientists, software engineers, and other stakeholders to integrate machine learning solutions into production environments.
- Utilize Azure cloud platform and containerization technologies (e.g., Docker, Kubernetes) for model deployment and management.
- Adhere to version control systems (e.g., Git) and agile software development methodologies.
Qualification
- Bachelor's degree or equivalent combination of education and experience