Machine Learning

at Capital Squared

Machine Learning

Capital Squared

Company

Home

Machine Learning

at Capital Squared

Posted by Hiring Team

5 - 10 yrs

₹25L - ₹55L / yr

Remote only

Skills

Python

Scikit-Learn

pandas

PostgreSQL

Data engineering

Time series

MLOps

Machine Learning (ML)

Full-Stack Machine Learning Engineer

Role: Full-Time, Long-Term Required: Python Preferred: C++

OVERVIEW

We are seeking a versatile ML engineer to join as a core member of our technical team. This is a long-term position for someone who wants to build sophisticated production systems and grow with a small, focused team. You will work across the entire stack—from data ingestion and feature engineering through model training, validation, and deployment.

The ideal candidate combines strong software engineering fundamentals with deep ML expertise, particularly in time series forecasting and quantitative applications. You should be comfortable operating independently, making architectural decisions, and owning systems end-to-end.

CORE TECHNICAL REQUIREMENTS

Python (Required): Professional-level proficiency writing clean, production-grade code—not just notebooks. Deep understanding of NumPy, Pandas, and their performance characteristics. You know when to use vectorized operations, understand memory management for large datasets, and can profile and optimize bottlenecks. Experience with async programming and multiprocessing is valuable.

Machine Learning (Required): Hands-on experience building and deploying ML systems in production. This goes beyond training models—you understand the full lifecycle: data validation, feature engineering, model selection, hyperparameter optimization, validation strategies, monitoring, and maintenance.

Specific experience we value: gradient boosting frameworks (LightGBM, XGBoost, CatBoost), time series forecasting, probabilistic prediction and uncertainty quantification, feature selection and dimensionality reduction, cross-validation strategies for non-IID data, model calibration.

You should understand overfitting deeply—not just as a concept but as something you actively defend against through proper validation, regularization, and architectural choices.

Data Pipelines (Required): Design and implement robust pipelines handling real-world messiness: missing data, late arrivals, schema changes, upstream failures. You understand idempotency, exactly-once semantics, and backfill strategies. Experience with workflow orchestration (Airflow, Prefect, Dagster) expected. Comfortable with ETL/ELT patterns, incremental vs full recomputation, data quality monitoring, database design and query optimization (PostgreSQL preferred), time series data at scale.

C++ (Preferred): Experience valuable for performance-critical components. Writing efficient C++ and interfacing with Python (pybind11, Cython) is a significant advantage.

HIGHLY DESIRABLE: MULTI-AGENT ORCHESTRATION

We are building systems leveraging LLM-based automation. Experience with multi-agent frameworks highly desirable: LangChain, LangGraph, or similar agent frameworks; designing reliable AI pipelines with error handling and fallbacks; prompt engineering and output parsing; managing context and state across agent interactions. You do not need to be an expert, but genuine interest and hands-on experience will set you apart.

DOMAIN EXPERIENCE: FINANCIAL DATA AND CRYPTO

Preference for candidates with experience in quantitative finance, algorithmic trading, or fintech; cryptocurrency markets and their unique characteristics; financial time series data and forecasting systems; market microstructure, volatility, and regime dynamics. This helps you understand why reproducibility is non-negotiable, why validation must account for temporal structure, and why production reliability cannot be an afterthought.

ENGINEERING STANDARDS

Code Quality: Readable, maintainable code others can modify. Proper version control (meaningful commits, branches, code review). Testing where appropriate. Documentation: docstrings, READMEs, decision records.

Production Mindset: Think about failure modes before they happen. Build in observability: logging, metrics, alerting. Design for reproducibility—same inputs produce same outputs.

Systems Thinking: Consider component interactions, not just isolated behavior. Understand tradeoffs: speed vs accuracy, flexibility vs simplicity. Zoom between architecture and implementation.

WHAT WE ARE LOOKING FOR

Self-Direction: Given a problem and context, you break it down, identify the path forward, and execute. You ask questions when genuinely blocked, not when you could find the answer yourself.

Long-Term Orientation: You think in years, not months. You make decisions considering future maintainability.

Intellectual Honesty: You acknowledge uncertainty and distinguish between what you know versus guess. When something fails, you dig into why.

Communication: You explain complex concepts clearly and document your reasoning.

EDUCATION

University degree in a quantitative/technical field preferred: Computer Science, Mathematics, Statistics, Physics, Engineering. Equivalent demonstrated expertise through work also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of a production ML system you built, (3) Links to relevant work if available, (4) Availability and timezone.

Full-Stack Machine Learning Engineer

Role: Full-Time, Long-Term Required: Python Preferred: C++

OVERVIEW

CORE TECHNICAL REQUIREMENTS

You should understand overfitting deeply—not just as a concept but as something you actively defend against through proper validation, regularization, and architectural choices.

C++ (Preferred): Experience valuable for performance-critical components. Writing efficient C++ and interfacing with Python (pybind11, Cython) is a significant advantage.

HIGHLY DESIRABLE: MULTI-AGENT ORCHESTRATION

DOMAIN EXPERIENCE: FINANCIAL DATA AND CRYPTO

ENGINEERING STANDARDS

Production Mindset: Think about failure modes before they happen. Build in observability: logging, metrics, alerting. Design for reproducibility—same inputs produce same outputs.

Systems Thinking: Consider component interactions, not just isolated behavior. Understand tradeoffs: speed vs accuracy, flexibility vs simplicity. Zoom between architecture and implementation.

WHAT WE ARE LOOKING FOR

Self-Direction: Given a problem and context, you break it down, identify the path forward, and execute. You ask questions when genuinely blocked, not when you could find the answer yourself.

Long-Term Orientation: You think in years, not months. You make decisions considering future maintainability.

Intellectual Honesty: You acknowledge uncertainty and distinguish between what you know versus guess. When something fails, you dig into why.

Communication: You explain complex concepts clearly and document your reasoning.

EDUCATION

University degree in a quantitative/technical field preferred: Computer Science, Mathematics, Statistics, Physics, Engineering. Equivalent demonstrated expertise through work also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of a production ML system you built, (3) Links to relevant work if available, (4) Availability and timezone.

Users love Cutshort

Read about what our users have to say about finding their next opportunity on Cutshort.

Shubham Vishwakarma

Full Stack Developer - Averlon

I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.

Companies hiring on Cutshort

About Capital Squared

Founded :

2025

Type :

Product

Size :

0-20

Stage :

Raised funding

About

At Capital Squared, our quant fund harnesses machine learning and deep learning to smartly invest in digital assets, aiming for consistent growth.

Company social profiles

N/A

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https://www.linkedin.com/in/purnendushekhar/">https://www.linkedin.com/in/purnendushekhar/
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Must have Prior knowledge and experience in Image processing and Video processing • Should have knowledge of object detection and recognition
Must have experience in feature extraction, segmentation and classification of the image
Face detection, alignment, recognition, tracking & attribute recognition
Excellent Understanding and project/job experience in Machine learning, particularly in areas of Deep Learning – CNN, RNN, TENSORFLOW, KERAS etc.
Real world expertise in deep learning- applied to Computer Vision problems • Strong foundation in Mathematics
Strong development skills in Python
Must have worked upon Vision and deep learning libraries and frameworks such as Opencv, Tensorflow, Pytorch, keras
Quick learner of new technologies
Ability to work independently as well as part of a team
Knowledge of working closely with Version Control(GIT)

Python Developer

at Kwantics

1 recruiter

Posted by Anant Tripathi

Noida, NCR (Delhi | Gurgaon | Noida)

1 - 3 yrs

₹5L - ₹7L / yr

Python

Data Science

Machine Learning (ML)

1. The candidate will work on building RNN based speech recognition systems 2. The candidate will work on building NLP based solution suite for speech data analytics 3. Adhoc Python coding will be required on a regular basis to support the application and data science team.

Python Developer

at FuGenX Technologies

1 video

3 recruiters

Posted by Aradya S

Hyderabad, Bengaluru (Bangalore)

1 - 6 yrs

₹1.3L - ₹6.3L / yr

Python

MongoDB

Machine Learning (ML)

Natural Language Processing (NLP)

Artificial Intelligence (AI)

+2 more

3 or more years of experience in Python programming Good understanding of Object oriented programming concept. Should have working knowledge with flask and mongodb. At least 2 - 3years experience in Machine learning and NLP Proficient with machine learning and deep learning libraries like Pandas,Numpy,Scikit learn,Tensorflow, and Keras, Expertise into deep learning- neural networks would add advantages Proficient with Any Natural language processing library like NLTK or Spacy Hands-on technical experience of Artificial intelligence using open source programming languages and analytics software. Experience using data science techniques such as web scraping, text mining, natural language processing, machine learning, statistical modelling or image recognition Data visualisation skills, e.g. in Tableau or qlikview would add advantage.

Software Engineer

at CONCERTO.AI

1 recruiter

Posted by Bhargavi N

Bengaluru (Bangalore)

3 - 5 yrs

₹15L - ₹18L / yr

Java

Machine Learning (ML)

Python

Artificial Intelligence (AI)

The person will be responsible for implementing natural language processing and AI / Machine learning components, as well as integrating available open source components and APIs into the system. Primary responsibilities will include implementing the system following directions from the architect and the AI scientific team, testing and validating performance, and supporting modifications as needed. Development of tools for training AI and ML algorithms will also be a part of the responsibility of this individual. Education: Bachelors or Masters in Computer Science. Proficiency in Java, Python Experience: Minimum of three to four years experience in implementing machine learning and natural language processing algorithms or working with available open source AI/ML components.

Technical Architect - Machine Learning

at CONCERTO.AI

1 recruiter

Posted by Bhargavi N

Bengaluru (Bangalore)

4 - 8 yrs

₹20L - ₹25L / yr

Machine Learning (ML)

Artificial Intelligence (AI)

Product Development

Concerto AI is a global Enterprise AI company founded by a team of people with deep enterprise knowledge and expertize in AI technologies. Our products incorporate the state-of-the-art AI technologies such as fact extraction from unstructured data, deep QA, dialog management, behavioral modeling, personalization and recommendation. For more information visit www.concerto.ai The person will architect cutting edge cognitive systems integrating state of the art technologies in natural language processing, deep learning, dialog systems, and personalization and recommendation systems. The person will also need to implement some key components as required. This person will also serve as a technical lead and have responsibility to direct the work of other technical team members in order to deliver a product package to specifications within targeted deadlines and level of effort.

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