JB001839 Senior Machine Learning Engineer Pan India · Remote

Techila Global; India; Remote; INR 2,500,000 - 4,500,000; Full time

Job summary

Techila Global is seeking a Senior Machine Learning Engineer to design, develop, and deploy scalable ML systems for demand forecasting and AI products. You will build end-to-end pipelines, manage data prep, experimentation, training, deployment, and monitoring in production.

You’ll work with PySpark, Databricks, PyTorch or TensorFlow, and multimodal data sources, ensuring reliability, observability, and collaboration with Applied Scientists.

Qualifications

• Significant experience designing and deploying machine learning systems in production environments.
• Train and productionise deep learning models using modern architectures such as Transformers, foundation models, and other representation learning approaches.

Responsibilities

• Design, develop, and deploy scalable machine learning systems that power demand forecasting and related AI products.
• Build and optimize large-scale data processing and feature engineering pipelines using PySpark and Databricks.

Skills

Python

PySpark

Databricks

PyTorch

TensorFlow

ML pipelines

Distributed computing

Tools

PySpark

Databricks

PyTorch

TensorFlow

Job description

# Senior Machine Learning EngineerJoin Techila's team of Salesforce experts. We build senior-led transformations that deliver measurable outcomes for clients worldwide.Apply Now →← All JobsExperience6–8 yrsEmployment TypeFull-timeOpenings1 positionApply ByOct 29, 2026## Required SkillsPython## Job DescriptionDesign, develop, and deploy scalable machine learning systems that power demand forecasting and related AI products.Design and maintain reliable ML workflows across the model lifecycle, including data preparation, experimentation, training, evaluation, deployment, inference, monitoring, and continuous improvement.Build and optimise large-scale data processing and feature engineering pipelines using technologies such as PySpark and Databricks, enabling efficient preparation of training and inference datasets.Develop multimodal machine learning solutions that combine diverse data sources, including product images, text, structured metadata, and behavioural signals, to create rich representations for downstream AI applications.Train and productionise deep learning models using modern architectures such as Transformers, foundation models, and other representation learning approaches.Partner with Applied Scientists to translate new modelling approaches into reliable, scalable production systems.Improve the performance, reliability, scalability, and observability of ML systems operating in production.Drive engineering excellence through architecture discussions, code reviews, mentoring, and knowledge sharing.About YouYou'll likely have:Significant experience designing and deploying machine learning systems in production environments.Strong software engineering skills in Python, with experience building maintainable, tested, and production-quality code.Strong experience with large-scale data processing using technologies such as PySpark and Databricks.Experience designing and building ML pipelines across the full lifecycle, from data preparation and model development through to deployment and monitoring.Experience developing deep learning models using frameworks such as PyTorch, TensorFlow, or similar.Experience with multimodal machine learning, representation learning, or embedding models, combining data sources such as images, text, structured metadata, or behavioural signals.Strong understanding of modern deep learning architectures, particularly Transformers, foundation models, multimodal learning, and representation learning techniques.Experience working with distributed computing, large datasets, and scalable model training or inference systems.Familiarity with cloud platforms and modern MLOps practices.Strong communication skills and the ability to collaborate effectively with scientists and engineers.A pragmatic mindset, balancing technical excellence with delivering business value.### At a GlanceWork ModeRemoteEmploymentFull-timeExperience6–8 yrsOpenings1DeadlineOct 29, 2026Apply for this Role →[ Hiring process ]## What to expectFour stages, typically completed within **2–3 weeks**. We respect your time — every stage has a clear purpose and timely feedback.1. STEP 0130 min ### Screening Call Introductory conversation with our talent team to understand your background and motivations.2. STEP 0260–90 min ### Technical Round Live problem-solving with a senior architect on Salesforce design, integrations, or domain depth.3. STEP 0345 min ### Culture Fit Conversation with practice leadership covering working style, ownership, and how you collaborate.4. STEP 04Within 5 days ### Offer Formal offer with full compensation breakdown, start date, and onboarding plan.Apply