AI/ML Engineer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Indus Valley, is seeking the following. Apply via Dice today!

The Lead AI/ML Engineer requires a unique mix of software engineering and machine learning skills necessary to create, deploy and maintain computationally efficient ML implementations, frameworks, tools and end-to-end solutions. This role has a specific focus on emerging artificial intelligence implementation into our tools and platforms. A strong understanding of math, algorithms, ML and data pipelines along with DevOps & MLOps best practices that will scale across many users and/or large, complex, and diverse data sets is critical to success.

Responsibilities:

Technical ML Engineer lead on larger projects that can span months

Foster a collaborative and innovative team environment, encouraging professional growth and development among junior team members.

Leverage known patterns, frameworks, and tools for automating & deploying machine learning solutions

Develop new tools, processes and operational capabilities to monitor and analyze model performance and data accuracy where needed

Work with researchers to optimize and scale Machine Learning Solutions using best practices in DevOps & MLOps

Abstract ML solutions as packages, APIs, or components that could be reused across the business

Build, steward, and maintain production-grade solutions (robust, reliable, maintainable, observable, scalable, performant etc.) to manage and serve machine learning models and science solutions

Research state of the art artificial intelligence and machine learning algorithms, patterns, processes, and tooling to identify new opportunities for implementation across the enterprise.

Serve as early adopter of new machine learning tools, platforms, and processes.

Understand business requirements and trade-off scale, risk, and accuracy to maximize value and translate research into consumable products or services

Reduce time to delivery, automate ML pipelines, and implement continuous feedback & monitoring practices

Responsible for code/science reviews and QA sign off

Apply appropriate documentation, version control, and other internal communication practices across channels.

Make time-sensitive decisions and solve urgent problems without escalation.

Qualifications, Skills, and Experience:

Bachelor s degree or higher in Machine Learning, Computer Science, Computer Engineering, Applied Statistics, or related field.

4+ years of experience developing cloud-based software solutions and an understanding of design for scalability, performance, and reliability.

4+ years of experience using advanced algorithms, programming languages, or technologies

2+ yrs hands-on experience building large-scale ML models, preferably as a data scientist; 2+ years of experience in emerging AI preferred

2+ years of experience in tech consulting, retail or related professional services preferred

Hands-on experience in the full end to end SDLC developing software solutions that scale and leverage CI/CD and MLOps to develop, test, and deploy.

Experience building large-scale algorithmic solutions that have been successfully delivered to stakeholders.

Excellent communication skills, particularly on technical topics.

Strong time and project management skills; the ability to balance multiple, simultaneous work items and prioritize as necessary.

Knowledge of deep learning methods is highly preferred.

Working experience in one or more ML frameworks such as PyTorch, TensorFlow, MLLib, and MLFlow

Knowledge of E2E Machine Learning pipeline and MLOps tools (e.g. Model registry, Experiment tracking, feature store, model monitoring)

Hands-on experience with technologies such as Azure, Spark, Nvidia Triton and Databricks

Strong skills in Python

Kubernetes & Docker experience

CI/CD Pipeline experience; Github Actions a plus

Terraform experience

API development experience a plus

Best Regards,

Rasmita Lima

(Office)