Machine Learning Expert (Contractor)

Location: Global, fully remote

Pay : $80/hour

Job Type: Contractor (~15 hours/week)

Schedule: Flexible — choose your own hours and days, including weekends

About the Role

We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python.

The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements.

This role is designed for experienced ML engineers and researchers who understand the systems beneath high-level APIs. Candidates should have deep, hands-on experience with multiple tools from the modern ML stack and be able to clearly explain what they personally built, optimized, or operated.

What You'll Work On

1. Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
2. Implement model components, data pipelines, evaluation systems, and numerical methods.
3. Build reproducible programmatic workflows using Python and command-line tools.
4. Work with tensor operations, automatic differentiation, model architectures, tokenization, batching, and generation.
5. Optimize training or inference for latency, throughput, memory usage, and hardware utilization.
6. Diagnose numerical instability, incorrect tensor behavior, memory bottlenecks, distributed-system failures, and performance regressions.
7. Compare model implementations and determine whether results are correct and reproducible.
8.



Review AI-generated code and technical solutions for correctness, efficiency, and engineering quality.
9. Design objective tests, benchmarks, and verification criteria.
10. Clearly document technical decisions, trade-offs, and limitations.

Required Qualifications
1. Minimum 8 years of professional or research experience in machine learning or a closely related technical field.
2. A master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline (equivalent experience considered in lieu of an advanced degree, given the required years of experience).
3. Advanced, professional-level proficiency with Python.
4. Meaningful, hands-on experience with at least two relevant ML frameworks, libraries, or inference tools.
5. Deep understanding of model training, evaluation, numerical computation, or inference systems.
6. Demonstrated ability to debug ML systems beyond surface-level API usage.
7. Strong ability to explain implementation decisions, performance trade-offs, and failure modes clearly and precisely.
8. Track record of building reproducible technical workflows.
9. History of technical leadership, senior IC ownership, or architectural decision-making on ML systems commensurate with seniority.

Relevant Tools (proficiency with 2+ expected)
- PyTorch
- JAX
- NumPy and SciPy
- SGLang
- vLLM
- llama.cpp
- Hugging Face Transformers
- Hugging Face Tokenizers

Equivalent tools may also be considered when the candidate demonstrates directly relevant depth. Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering workplace is strongly preferred. Exceptional open-source or academic experience of comparable depth may also qualify.

Process

1. Apply to the role and complete the screening questions.
2. Complete an AI interview (~30 minutes).
3. Complete a technical assessment, if required.
4. Complete the hiring manager review.

📌 Senior Machine Learning Engineer (Mumbai)
🏢 Kaliper
📍 Mumbai