Blockchain Data & ML Engineer at Deqode · Indore · 0 - 2 years · ₹6L - ₹12L / yr · Bootstrapped · Posted 27 Jun 2025

About Us
Alfred Capital - Alfred Capital is a next-generation on-chain proprietary quantitative trading technology provider, pioneering fully autonomous algorithmic systems that reshape trading and capital allocation in decentralized finance.
As a sister company of Deqode — a 400+ person blockchain innovation powerhouse — we operate at the cutting edge of quant research, distributed infrastructure, and high-frequency execution.
What We Build
- Alpha Discovery via On‑Chain Intelligence — Developing trading signals using blockchain data, CEX/DEX markets, and protocol mechanics.
- DeFi-Native Execution Agents — Automated systems that execute trades across decentralized platforms.
- ML-Augmented Infrastructure — Machine learning pipelines for real-time prediction, execution heuristics, and anomaly detection.
- High-Throughput Systems — Resilient, low-latency engines that operate 24/7 across EVM and non-EVM chains tuned for high-frequency trading (HFT) and real-time response
- Data-Driven MEV Analysis & Strategy — We analyze mempools, order flow, and validator behaviors to identify and capture MEV opportunities ethically—powering strategies that interact deeply with the mechanics of block production and inclusion.
Evaluation Process
- HR Discussion – A brief conversation to understand your motivation and alignment with the role.
- Initial Technical Interview – A quick round focused on fundamentals and problem-solving approach.
- Take-Home Assignment – Assesses research ability, learning agility, and structured thinking.
- Assignment Presentation – Deep-dive into your solution, design choices, and technical reasoning.
- Final Interview – A concluding round to explore your background, interests, and team fit in depth.
- Optional Interview – In specific cases, an additional round may be scheduled to clarify certain aspects or conduct further assessment before making a final decision.
Blockchain Data & ML Engineer
As a Blockchain Data & ML Engineer, you’ll work on ingesting and modeling on-chain behavior, building scalable data pipelines, and designing systems that support intelligent, autonomous market interaction.
What You’ll Work On
- Build and maintain ETL pipelines for ingesting and processing blockchain data.
- Assist in designing, training, and validating machine learning models for prediction and anomaly detection.
- Evaluate model performance, tune hyperparameters, and document experimental results.
- Develop monitoring tools to track model accuracy, data drift, and system health.
- Collaborate with infrastructure and execution teams to integrate ML components into production systems.
- Design and maintain databases and storage systems to efficiently manage large-scale datasets.
Ideal Traits
- Strong in data structures, algorithms, and core CS fundamentals.
- Proficiency in any programming language
- Curiosity about how blockchain systems and crypto markets work under the hood.
- Self-motivated, eager to experiment and learn in a dynamic environment.
Bonus Points For
- Hands-on experience with pandas, numpy, scikit-learn, or PyTorch.
- Side projects involving automated ML workflows, ETL pipelines, or crypto protocols.
- Participation in hackathons or open-source contributions.
What You’ll Gain
- Cutting-Edge Tech Stack: You'll work on modern infrastructure and stay up to date with the latest trends in technology.
- Idea-Driven Culture: We welcome and encourage fresh ideas. Your input is valued, and you're empowered to make an impact from day one.
- Ownership & Autonomy: You’ll have end-to-end ownership of projects. We trust our team and give them the freedom to make meaningful decisions.
- Impact-Focused: Your work won’t be buried under bureaucracy. You’ll see it go live and make a difference in days, not quarters
What We Value:
- Craftsmanship over shortcuts: We appreciate engineers who take the time to understand the problem deeply and build durable solutions—not just quick fixes.
- Depth over haste: If you're the kind of person who enjoys going one level deeper to really "get" how something works, you'll thrive here.
- Invested mindset: We're looking for people who don't just punch tickets, but care about the long-term success of the systems they build.
- Curiosity with follow-through: We admire those who take the time to explore and validate new ideas, not just skim the surface.
Compensation:
- INR 6 - 12 LPA
- Performance Bonuses: Linked to contribution, delivery, and impact.

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Job Description: Python + AI
Company: Wissen Technology
Location: Bangalore, India
Experience: 5+Years
Employment Type: Full-Time
Role: Python + AI / Data Engineer
About the Role
Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.
The candidate should be capable of designing and developing scalable data and AI solutions, building robust ETL/ELT pipelines, working with large datasets, and integrating AI/ML capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and PySpark.
- Develop robust ETL/ELT pipelines for processing large volumes of structured and unstructured data.
- Build and optimize data processing solutions using Apache Spark / PySpark.
- Develop data ingestion and transformation pipelines into Snowflake.
- Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
- Work with batch and, where applicable, real-time data processing pipelines.
- Build and integrate AI and Generative AI solutions using Python.
- Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
- Integrate AI models with enterprise data platforms and data pipelines.
- Develop REST APIs and microservices using FastAPI, Flask, or Django.
- Perform data cleansing, transformation, validation, and quality checks.
- Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
- Implement data pipeline monitoring, logging, error handling, and alerting.
- Work with cloud platforms such as AWS, Azure, or GCP.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
- Participate in technical design, architecture, code reviews, and production support.
- Mentor junior engineers and contribute to engineering best practices.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
- Experience working on enterprise-scale AI and data engineering projects.
- Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
- Experience with Databricks is an advantage.
- Experience with AI Agents / Agentic AI and tool/function calling.
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ML DEVELOPER
Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.
JOB OVERVIEW
We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future.
The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.
RESPONSIBILITIES:
- Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
- Develop custom evals for AI agents.
- Build and maintain ML pipelines
- Optimize and evaluate ML models to ensure accuracy and performance.
- Define system requirements and integrate ML algorithms into cloud based workflows.
- Write clean, well-documented, and maintainable code following best practices
REQUIREMENTS:
- 2-3+ years of experience in data science, machine learning, or a similar role.
- Demonstrated expertise with python, PyTorch, and TensorFlow.
- Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
- Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
- Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc
WHO CAN APPLY:
Only those candidates will be considered who,
- have relevant skills and interests
- can commit full time
- Can show prior work and deployed projects
- can start immediately
Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.
SALARY DETAILS: Commensurate with experience.
JOINING DATE: Immediate
JOB TYPE: Full-time
Description
We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.
Responsibilities
- Design, build, and deploy scalable machine learning models into production systems.
- Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
- Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
- Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
- Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
- Optimize query performance, storage usage, and data pipelines for efficiency.
- Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
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Requirements
- Minimum 5 years of experience in Data Science or Applied Machine Learning.
- Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
- Proven expertise in deploying ML models into production systems.
- Experience with big data platforms (Hadoop, Spark) and distributed data processing.
- Hands-on experience with Databricks, Airflow, and AWS EMR.
- Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
- Solid understanding of query optimization, storage systems, and data pipelines.
- Excellent problem-solving skills, with the ability to design scalable solutions.
- Strong communication and collaboration skills to work in cross-functional teams.
Benefits
- Best-in-class salary: We hire strong talent and compensate accordingly.
- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
- High-impact work: Build AI-first systems and products used at scale by global clients.
About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.
KEY RESPONSIBILITIES
End-to-End ML Development
• Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.
• Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.
• Validate model performance using appropriate statistical techniques and domain knowledge.
MLOps & Production Deployment
• Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.
• Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.
• Ensure model reliability, observability, and performance in live production environments.
Language Models & LLM Applications
• Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.
• Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.
• Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.
• Support exploratory work around LLM integration and prompt engineering for internal tooling.
Domain-Driven Analytics
• Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.
• Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.
• Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.
REQUIRED QUALIFICATIONS
Education
• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.
Experience
• 2–4 years of hands-on experience in a data science or machine learning role.
• Demonstrable experience deploying ML models in production environments (not just prototyping).
Technical Skills
• Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).
• Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.
• Hands-on experience with BERT-family models and Hugging Face Transformers library.
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.
• Solid understanding of SQL and working with large structured/unstructured datasets.
• Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).
GOOD TO HAVE
• Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).
• Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.
• Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.
• Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).
• Contributions to open-source ML projects or published research.
THIS ROLE IS NOT FOR YOU IF…
• You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.
• Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.
Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
Job Title: Senior AI/ML Engineer
Company: Timble Technologies Pvt. Ltd
Location: Gurugram (Hybrid)
Experience: 2 TO 5 Years
About Us
Timble Glance is a high-growth AI RegTech and B2B SaaS company catering to top-tier BFSI and enterprise clients. We build cutting-edge systems powering 30+ high-scale APIs for digital identity verification, fraud detection, document intelligence, and compliance automation.
Role Overview
We are looking for a hands-on Senior AI/ML Engineer to design, develop, and productionize high-throughput AI/ML and Generative AI systems. You will own the full lifecycle—from problem formulation and data pipelines to deep learning architectures, RAG systems, LLMOps, and model governance—delivering sub-second latency and high reliability across our enterprise products.
Key Responsibilities
· Model Architecture & Deployment: Design, train, and deploy production-scale ML/Deep Learning and GenAI systems (computer vision, document intelligence, OCR, NLP, fraud risk classification, and LLM applications).
· GenAI & LLM Solutions: Develop robust LLM workflows including prompt engineering, fine-tuning, RAG pipelines, semantic search, vector indexing (Pinecone/Milvus/Chroma), and safety guardrails.
· Pipelines & Engineering: Build performant feature extraction and data pipelines; write modular, vectorized, production-grade Python (NumPy, Pandas) and advanced SQL.
· MLOps & Monitoring: Establish end-to-end MLOps/LLMOps standards—model registries, CI/CD, experiment tracking, drift detection, A/B testing, latency optimization, and cost governance.
· Responsible AI & Security: Ensure model decisions comply with enterprise data security, privacy standards, and auditability required by the BFSI sector.
· Collaboration & Ownership: Translate complex business requirements into technical roadmaps, conduct rigorous code reviews, and mentor junior engineers.
Required Qualifications & Skills
· Education: B.Tech / M.Tech in Computer Science, AI/ML, Mathematics, or a related field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.
· Experience: 2+ years of hands-on experience developing, deploying, and maintaining ML/Deep Learning or GenAI models in production environments.
· GenAI & NLP Stack: Hands-on experience with LLMs, embeddings, RAG architectures, and frameworks such as LangChain, LlamaIndex, or Hugging Face.
· Deep Learning Frameworks: Strong proficiency in PyTorch or TensorFlow, with deep knowledge of transformer architectures and modern NLP/CV models.
· Software & Data Engineering: Expert-level Python skills (pytest, Git, OOP, asynchronous programming), solid SQL proficiency, and familiarity with data workflows.
· Deployment & Cloud: Practical exposure to cloud platforms (AWS/GCP), containerization (Docker), API frameworks (FastAPI/Flask), and basic orchestration (Kubernetes).
Preferred Qualifications
· Prior domain experience in Fintech, RegTech, Identity Verification (KYC/AML), Fraud Intelligence, or B2B SaaS.
· Experience optimizing models for low latency and inference cost (e.g., ONNX, TensorRT, model quantization).
· Familiarity with workflow orchestrators such as Airflow, Prefect, or Kubeflow.
Job Summary
We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.
Key Responsibilities
- Design, develop, and maintain ETL/ELT data pipelines.
- Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
- Develop automation scripts using Python for data processing and workflow optimization.
- Work with Linux environments for deployment, monitoring, and troubleshooting.
- Ensure data quality, integrity, and reliability across data platforms.
- Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
- Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
- Implement best practices for data security, governance, and documentation.
Required Skills
- Strong experience in Data Engineering concepts and ETL/ELT processes.
- Proficiency in SQL, including query optimization and database design.
- Strong programming skills in Python.
- Hands-on experience with Linux commands, shell scripting, and system administration basics.
- Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
- Familiarity with Git/version control.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with cloud platforms (AWS, Azure, or GCP).
- Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
- Experience with data warehousing solutions and big data technologies.
- Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Relevant certifications in cloud or data engineering are an added advantage.
ABOUT
The Persona Labs is building a new kind of social platform focused on something most social products do not explicitly optimize for: helping people become real friends.
We want to help people discover interesting people around them, find meaningful common ground, start low-pressure interactions, continue promising conversations, create shared experiences, and ultimately build real-life friendships.
DISCOVER → CURIOSITY → COMPATIBILITY → INTERACTION → UNDERSTAND → IRL EXPERIENCE → FRIENDSHIP
THE AI LAYER - COMPANION INTELLIGENCE
Alongside the platform, we are building a proactive personal AI companion that learns about the user and helps them navigate this journey through personalized recommendations, suggestions, reminders, conversations, and experiences.
THE OPPORTUNITY
We are looking for a Founding ML Engineer to build the intelligence layer of the platform from the ground up. This is a 0→1 Applied AI / ML role where you will work directly with the founder and Product Engineer to turn ambiguous problems around users, relationships, recommendations and personal intelligence into working systems.
You will be expected to:
Understand the problem → identify the signals → design the intelligence system → prototype → evaluate → deploy → learn → improve.
WHAT YOU WILL BUILD & OWN
USER INTELLIGENCE
User representations, behavioural models, interests, preferences, contextual signals, and evolving understanding of the user. MEMORY Short- and long-term memory, episodic/preference/relationship memory, retrieval, relevance and updating.
RECOMMENDATION & MATCHING
People discovery, compatibility, activity/experience recommendations, and personalized ranking.
INTENT & INTEREST
Infer what the user is trying to do and learn what they care about from behaviour, not only declared interests.
RANKING
Decide what should appear first across potentially thousands of relevant people, activities or experiences.
CONTENT INTELLIGENCE
Classification, toxicity, spam, policy signals, quality, relevance, and semantic understanding.
RELATIONSHIP INTELLIGENCE
Reciprocity, interaction health, shared interests, progression, declining engagement and shared activity.
NEXT-BEST-ACTION
Determine the most useful action now: show a person, suggest a question, recommend an activity, reconnect, or do nothing.
TRUST / SAFETY INTELLIGENCE
Fake-account signals, spam, abuse, behavioural anomalies, risky interactions and moderation assistance.
COMPANION INTELLIGENCE
Use signals and outputs to help the companion decide what to say, suggest, recommend or not do.
WHAT YOUR DAY-TO-DAY LOOKS LIKE
• Translate ambiguous product problems into ML/AI system designs.
• Build models and intelligence pipelines using behavioural, relational and contextual signals.
• Develop recommendation, matching and personalization systems.
• Design memory and retrieval systems that help the companion understand the user over time.
• Build and evaluate LLM-powered and agentic workflows.
• Decide when to use traditional ML, rules, retrieval, ranking or LLMs.
• Prototype quickly, test assumptions and iterate based on real user behaviour.
• Work closely with the founder and Product Engineer to turn intelligence into product experiences.
• Design APIs and production systems that bring ML/AI capabilities into the application.
• Build evaluation, monitoring and feedback loops so the intelligence improves over time.
WHO SHOULD APPLY
• Experience: 0–4 years’ experience, including exceptional fresh graduates. Strong 1–3 year engineers and experienced 3–4 year product builders are welcome.
• Strong foundations in ML, Python, statistics and software engineering.
• Evidence of Building: Experience with AI/ML projects, recommendation systems, LLM applications or personalization is highly valued.
• Strong evidence of building: Shipped projects, research, hackathons, internships, open source or startup work.
WHAT WE LOOK FOR
MACHINE LEARNING DEPTH
Can you understand the modelling problem underneath the application?
RECOMMENDATION & PERSONALIZATION
Can you reason about relevance, ranking, cold start and behavioural signals?
AI ENGINEERING
Can you turn LLMs and agents into reliable product capabilities rather than simple API wrappers?
USER INTELLIGENCE
Can you design systems that gradually understand a person from sparse and changing signals?
SYSTEMS THINKING
Can you move from a model to a production system with APIs, data, latency, cost and monitoring?
EVALUATION MINDSET
Can you determine whether the intelligence actually helped the user?
PRODUCT JUDGMENT
Can you decide what the system should do when there is no predefined answer?
SPEED OF EXECUTION
Can you move from idea → prototype → evaluation → production quickly and responsibly?
BUILD WITH US
You will join at a stage where many of the answers do not exist yet. You will not simply implement a model someone else selected; you will help decide how the product learns to understand people.
CAREERS:
Apply with your resume, GitHub, portfolio or shipped work.
https://forms.gle/12YpUSBY2Sqs5xjp8
www.thepersonalabs.com
This is a remote position.
About Leegality:
Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.
We have multiple products across 2 categories:
Document Infrastructure:
Products that help businesses build paperless processes at scale:
- Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
- Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contract
- Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner
Consent Infrastructure:
- Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
- Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.
If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.
Curious about our impact? Explore our customer success stories: leegality.com/case-studies
Our Culture
At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.
We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:
- Flexible working hours
- Hybrid work setup
- Bi-annual performance appraisals
- A culture that rewards initiative, curiosity, and impact
If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.
Location: Hybrid
Job Brief:
- As a Machine Learning Engineer specializing in Computer Vision (CV) and Natural Language Processing (NLP), you will develop solutions to interesting technical problems, exploring exciting growth opportunities and having a real impact on our product, particularly focusing on document and content intelligence.
- To ensure success, you should demonstrate solid data science knowledge and experience in a related ML, CV, or NLP role. A first-class engineer will be someone whose expertise enhances our systems for document intelligence and content processing
Responsibilities:
- Designing machine learning systems, self-running artificial intelligence (AI) software, and specialized models for Computer Vision and Natural Language Processing applications.
- Transforming data science prototypes and applying appropriate deep learning algorithms and tools to text and image/document data.
- Solving complex CV and NLP problems with multi-layered data types, such as image/document classification, information extraction, semantic search, and object detection.
- Optimizing existing machine learning models, with a focus on high-performance model deployment for CV and NLP tasks.
- Developing ML algorithms (including large language models/LLMs and computer vision models) to analyze huge volumes of historical text, image, and document data to make predictions and automate workflows.
- Running tests, performing statistical analysis, and interpreting test results for CV/NLP model performance.
- Documenting machine learning processes, model architectures, and data pipelines.
- Keeping abreast of developments in machine learning, Computer Vision, and Natural Language Processing.
Requirements:
- 3+ years of relevant experience in Machine Learning Engineering, with a strong focus on Computer Vision and/or Natural Language Processing.
- Advanced proficiency with Python.
- Extensive knowledge of ML frameworks, libraries (e.g., PyTorch, Transformers), data structures, data modeling, and software architecture.
- Experience with building and maintaining scalable RESTful APIs (e.g., FastAPI).
- In-depth knowledge of mathematics, statistics, deep learning (CNNs, RNNs, Transformers), and algorithms.
- Superb analytical and problem-solving abilities, especially for unstructured data challenges.
- Great communication and collaboration skills.
- Excellent time management and organizational abilities.
- Experience with cloud platforms (e.g., AWS) for model deployment and MLOps.
Recruitment Process:
- Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
- You will be contacted via email with the next steps upon being shortlisted.
- The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
- Final selection and CTC will be based on your overall performance and experience.
Apply directly through our career page: https://careers.leegality.com/jobs/Careers
For more information about us please visit our:
Our Company and Culture: https://bit.ly/3Iqm5SB
Our Website: www.leegality.com/
Our LinkedIn Page: www.linkedin.com/company/leegality/
Leegality's Privacy Notice: https://www.leegality.com/employee-privacy-notice













