Machine Learning Engineer (US)

AVP VIGILANT TECHNOLOGY PVT LTD; New York (NY); Hybrid; USD 120,000 - 250,000; Full time

Benefits offered by this job

Medical insurance

401(k)

Paid time off

Job summary

AVP Vigilant Technology Pvt Ltd is seeking a Machine Learning Engineer to design, build, deploy, and optimize ML solutions. You will work across data, model development, software engineering, and MLOps to bring ML models from experimentation into production systems in a hybrid US-based role.

The ideal candidate has 2–8 years of experience, strong Python skills, hands-on experience with scikit-learn, PyTorch, or TensorFlow, plus ML deployment, CI/CD, model monitoring, and cloud platforms

Qualifications

• 2-8 years of experience in Machine Learning Engineering, Software Engineering, Data Science, or a related field.
• Strong proficiency in Python and experience with ML libraries such as scikit-learn, PyTorch, or TensorFlow.
• Hands-on experience deploying ML models into production.

Responsibilities

• Develop, train, evaluate, and optimize machine learning models.
• Build scalable ML pipelines for data preparation, training, validation, and deployment.
• Productionize ML models and monitor performance, reliability, and model drift.
• Implement MLOps practices for automated model deployment and lifecycle management.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, and Product teams.
• Improve model accuracy, scalability, latency, and overall system performance.

Skills

Python

ML libraries

Model deployment

MLOps

SQL

Cloud platforms

Software engineering

Tools

Kubernetes

Docker

Airflow

MLflow

Kubeflow

Job description

Machine Learning Engineer

Experience: 2-8 Years

Location: San Francisco, CA | Seattle, WA | New York, NY | Boston, MA

Salary: $120,000-$250,000+ per year

Job Type: Full-Time

About The Role

We are seeking a talented Machine Learning Engineer to design, build, deploy, and optimize machine learning solutions that solve real-world business and technical problems. You'll work across data, model development, software engineering, and MLOps to bring ML models from experimentation into reliable production systems.

Key Responsibilities

• Develop, train, evaluate, and optimize machine learning models.
• Build scalable ML pipelines for data preparation, training, validation, and deployment.
• Productionize ML models and monitor performance, reliability, and model drift.
• Implement MLOps practices for automated model deployment and lifecycle management.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, and Product teams.
• Improve model accuracy, scalability, latency, and overall system performance.
• Design APIs and services for integrating ML models into production applications.
• Implement testing, CI/CD, version control, and automated ML workflows.
• Troubleshoot production ML systems and continuously improve reliability.
• Stay current with emerging machine learning, MLOps, and AI technologies.

Required Qualifications

• 2-8 years of experience in Machine Learning Engineering, Software Engineering, Data Science, or a related field.
• Strong proficiency in Python and experience with ML libraries such as scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of machine learning algorithms, statistics, model evaluation, and optimization.
• Hands-on experience building and deploying ML models into production.
• Experience with MLOps, ML pipelines, model monitoring, and CI/CD.
• Strong SQL and data-processing skills.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong software engineering, debugging, and problem-solving skills.

Preferred Qualifications

• Experience with Kubernetes, Docker, Airflow, MLflow, Kubeflow, or similar tools.
• Experience with feature stores and model-serving platforms.
• Knowledge of distributed computing and large-scale data processing.
• Experience with Generative AI, LLMs, RAG, NLP, or computer vision.
• Experience optimizing ML systems for production-scale workloads.

What We Offer

• Competitive salary of $120K-$250K+, based on experience, skills, and location.
• Medical, dental, and vision insurance.
• 401(k) and retirement benefits.
• Paid time off and company holidays.
• Flexible and hybrid work options, depending on role.
• Professional development and learning opportunities.
• Opportunity to work on high-impact AI and ML products.
• Collaborative, technology-driven work environment.

Skills: ml,machine learning,data