AI/ML Engineer

Mphasis; New York (NY); On-site; USD 120,000 - 140,000; Full time

Job summary

Mphasis is seeking an AI/ML Engineer with 4-5 years of experience to develop and optimize scalable machine learning solutions. The role includes automating ML processes and contributing to MLOps practices. Applicants should have strong skills in Python, familiarity with ML frameworks, and a commitment to advancing ML systems.

Benefits

Medical insurance

Vision insurance

Qualifications

• 4-5 years of hands-on experience in building and deploying scalable ML solutions.
• Strong programming skills in Python with ML frameworks experience.
• Familiarity with MLOps practices and cloud-native technologies.

Responsibilities

• Automate deployment, monitoring, and retraining of ML models.
• Design and deploy scalable ML tools tailored to client needs.
• Drive continuous improvement of MLOps pipelines.

Skills

Python

MLOps

Machine Learning

Data Architecture

Data Management

Analytical Skills

Problem Solving

Education

Bachelor’s or Master’s Degree in Computer Science, Data Science, or related field

Tools

TensorFlow

PyTorch

scikit-learn

MLflow

Kubeflow

Docker

Kubernetes

Job description

This range is provided by Mphasis. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$120,000.00/yr - $140,000.00/yr

Direct message the job poster from Mphasis

Location : Onsite - Dallas, TX and NJ/NY

This is Fulltime role with Mphasis

NOTE: WE ARE NOT SPONSORING ANY VISA FOR THIS ROLE.

Who are we looking For:

We are seeking a skilled and motivated AI/ML Engineer with 4–5 years of hands-on experience in building and deploying scalable machine learning solutions. The ideal candidate will have a deep understanding of the end-to-end ML lifecycle, MLOps practices, and cloud-native technologies. You will play a critical role in automating, scaling, and optimizing our clients’ machine learning systems, and contribute to advancing MLOps maturity across the organization.

Key Responsibilities:

· Automate the deployment, monitoring, and retraining machine learning models across various environments.

· Design, develop, and deploy scalable ML tools and services for training and inference tailored to client needs.

· Identify and evaluate emerging technologies to enhance the performance, scalability, and reliability of ML systems.

· Drive continuous improvement of MLOps pipelines, ensuring alignment with industry best practices.

· Troubleshoot issues throughout the ML lifecycle—from data preprocessing to model serving—within MLOps frameworks.

· Implement monitoring and detection mechanisms for data drift and model drift.

· Contribute to internal research initiatives and best practice frameworks to elevate organizational MLOps maturity.

· Prepare documentation and deliver presentations on MLOps tools, processes, and enhancements.

Technical Skills – Must Have

· Bachelor’s or master’s degree in computer science, Data Science, or a related field.

· Strong programming skills in Python with hands-on experience in ML frameworks such as TensorFlow, PyTorch, and scikit-learn.

· Experience with ML workflow orchestration tools like MLflow or Kubeflow.

· Solid understanding of data architecture, data engineering, and data management practices.

· Familiarity with tools and processes used by data scientists, with experience in software development and test automation.

· Proven ability to design and implement MLOps pipelines in cloud environments such as AWS, Azure, or GCP.

· Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).

· Strong analytical and problem-solving abilities to address complex system-level challenges.

· Excellent communication and interpersonal skills, with the ability to convey technical concepts to diverse stakeholders.

Technical Skills - Good to have

Preferred Qualifications:

· Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.

· A portfolio showcasing AI/ML and NLP projects.

Process Skills:

· Understanding of utilizing Agile and Scrum software development methodologies

· Skill in gathering and documenting user requirements and writing technical specifications.

Behavioral Skills:

· Work closely with designers, Architects, data scientists, product managers, and other engineers to deliver comprehensive solutions.

· Strong problem-solving skills, with a creative approach to tackling complex challenges.

· Communicate effectively and share technical knowledge with the team.

· Be open to feedback and continuously learn and adapt to new technologies.

· Ability to work independently and as part of a team.

· Passion for learning and staying updated on the latest technologies.

· Good Attitude and Quick learner .

Certification(Good to have) :

· Cloud development certification (Any of GCP, Azure or AWS)

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Finance, Distribution, and Consulting

• Industries

  IT Services and IT Consulting

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Vision insurance

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