[Remote] Delivery Manager - DS/ML - India at Turing

India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Machine Learning, TechnologyIndustries

Requirements

10+ years of experience in engineering, program management, or AI delivery, including 2+ years in ML/LLM project leadership
Proven ability to manage large-scale delivery programs (100+ team members) across data, research, and engineering streams
Strong technical grounding in machine learning, NLP, and modern deep learning frameworks (PyTorch, TensorFlow, Hugging Face, etc.)
Working knowledge of MLOps pipelines (MLflow, Kubeflow, or Vertex AI) and cloud platforms

Responsibilities

Lead and manage large, cross-functional ML delivery teams (ML engineers, data scientists, MLOps, and annotators)
Build scalable organizational structures and delivery mechanisms to support multiple concurrent ML/LLM programs
Define clear KPIs, quality goals, and success metrics for every project stage
Drive a culture of ownership, learning, and technical excellence through coaching, recognition, and gamified performance systems
Own end-to-end delivery of large-scale ML projects — from planning and training through deployment and monitoring
Translate research and product goals into executable delivery roadmaps
Identify and resolve risks, blockers, and dependencies proactively
Provide transparent reporting to senior leadership and research partners on delivery status, risks, and quality
Ensure delivery excellence in data pipelines, model development, and evaluation frameworks
Review ML architectures and promote best practices in reproducibility, experiment tracking, and model governance
Analyze performance data and error trends to improve training efficiency and output quality
Champion continuous improvement and innovation in ML delivery workflows
Partner closely with AI researchers, data infrastructure, and product teams to translate research insights into production-grade ML systems
Collaborate with engineering leaders to streamline compute usage, tooling, and resource allocation
Contribute to design discussions around distributed training, fine-tuning, and scalable ML infrastructure
Document and disseminate learnings to accelerate organizational ML maturity

Skills

Key technologies and capabilities for this role

Machine LearningMLOpsLLM EngineeringData PreparationModel TrainingDeploymentPerformance OptimizationTeam LeadershipProject ManagementAI Research

Questions & Answers

Common questions about this position

Is this Delivery Manager role remote?

Yes, the position is remote and available in India or Brazil.

What salary or compensation does this role offer?

This information is not specified in the job description.

What key skills and experience are required for this Delivery Manager position?

The role requires a strong background in Machine Learning, MLOps, and LLM engineering, along with experience leading large cross-functional teams of ML engineers, data scientists, MLOps, and annotators.

What is the company culture like at Turing?

Turing fosters a culture of ownership, learning, and technical excellence through coaching, recognition, and gamified performance systems.

What makes a strong candidate for this Delivery Manager role?

A strong candidate is a strategic operator and technical leader who can bridge research, engineering, and business delivery, lead projects with 100+ team members, and ensure excellence in ML project execution from data preparation to deployment.

Turing

AI-driven matching of businesses with engineers

About Turing

Turing provides tech services by using artificial intelligence to connect businesses with skilled software engineers for custom application development and on-demand engineering needs. The company has a large pool of over 3 million vetted engineers from 150 countries, allowing businesses to quickly find the right talent for their projects. When a company needs a developer, they specify the required skills, and Turing's AI matches them with the best candidates, streamlining the recruitment process and helping companies complete projects faster. Turing also supports engineers by offering access to high-paying remote job opportunities in the U.S., with a high rematch rate ensuring job stability. The goal of Turing is to enhance recruitment efficiency for businesses while providing valuable job opportunities for engineers.

Palo Alto, CaliforniaHeadquarters

2018Year Founded

$132.3MTotal Funding

SERIES_DCompany Stage

Enterprise Software, AI & Machine LearningIndustries

1,001-5,000Employees

Risks

Competition from platforms like DevZero offering cloud-based development environments.

Crowded market with new AI-driven talent platforms like Gaper and Aloa.

Potential brand confusion with South Korean company Turing Co.

Differentiation

Turing uses AI to match businesses with over 3 million vetted engineers.

Turing's Talent Cloud accelerates team building, similar to scaling servers on AWS.

Turing offers a 99% rematch rate for engineers, ensuring job stability.

Upsides

Remote work trend boosts demand for Turing's remote engineer connections.

Global tech talent shortage increases reliance on Turing's AI-powered talent matching.

Turing's AI-driven recruitment tools enhance hiring efficiency and accuracy.

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