Business Developer

Strong Backend Developer with Rust knowledge

Mandatory (Experience) - Must have 3+ YOE as a Software Engineer

Mandatory (Core Skills) - Expert level knowledge in Rust or Realtime experience in Rust

Mandatory (Company) - Product company (Highly preferred- Blockchain companies, Gaming Companies, Early stage startups)

Mandatory (Education) - Engineering from Tier-1 Colleges

Hybrid work mode

(Azure) EDW Experience working in loading Star schema data warehouses using framework

architectures including experience loading type 2 dimensions. Ingesting data from various

sources (Structured and Semi Structured), hands on experience ingesting via APIs to lakehouse architectures.

Key Skills: Azure Databricks, Azure Data Factory, Azure Datalake Gen 2 Storage, SQL (expert),

Python (intermediate), Azure Cloud Services knowledge, data analysis (SQL), data warehousing,documentation – BRD, FRD, user story creation.

Senior Machine Learning Engineer

About the Role

We are looking for a Senior Machine Learning Engineer who can take business problems, design appropriate machine learning solutions, and make them work reliably in production environments.

This role is ideal for someone who not only understands machine learning models, but also knows when and how ML should be applied, what trade-offs to make, and how to take ownership from problem understanding to production deployment.

Beyond technical skills, we need someone who can lead a team of ML Engineers, design end-to-end ML solutions, and clearly communicate decisions and outcomes to both engineering teams and business stakeholders. If you enjoy solving real problems, making pragmatic decisions, and owning outcomes from idea to deployment, this role is for you.

What You’ll Be Doing

Building and Deploying ML Models

• Design, build, evaluate, deploy, and monitor machine learning models for real production use cases.
• Take ownership of how a problem is approached, including deciding whether ML is the right solution and what type of ML approach fits the problem.
• Ensure scalability, reliability, and efficiency of ML pipelines across cloud and on-prem environments.
• Work with data engineers to design and validate data pipelines that feed ML systems.
• Optimize solutions for accuracy, performance, cost, and maintainability, not just model metrics.

Leading and Architecting ML Solutions

• Lead a team of ML Engineers, providing technical direction, mentorship, and review of ML approaches.
• Architect ML solutions that integrate seamlessly with business applications and existing systems.
• Ensure models and solutions are explainable, auditable, and aligned with business goals.
• Drive best practices in MLOps, including CI/CD, model monitoring, retraining strategies, and operational readiness.
• Set clear standards for how ML problems are framed, solved, and delivered within the team.

Collaborating and Communicating

• Work closely with business stakeholders to understand problem statements, constraints, and success criteria.
• Translate business problems into clear ML objectives, inputs, and expected outputs.
• Collaborate with software engineers, data engineers, platform engineers, and product managers to integrate ML solutions into production systems.
• Present ML decisions, trade-offs, and outcomes to non-technical stakeholders in a simple and understandable way.

What We’re Looking For

Machine Learning Expertise

• Strong understanding of supervised and unsupervised learning, deep learning, NLP techniques, and large language models (LLMs).
• Experience choosing appropriate modeling approaches based on the problem, available data, and business constraints.
• Experience training, fine-tuning, and deploying ML and LLM models for real-world use cases.
• Proficiency in common ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.

Production and Cloud Deployment

• Hands-on experience deploying and running ML systems in production environments on AWS, GCP, or Azure.
• Good understanding of MLOps practices, including CI/CD for ML models, monitoring, and retraining workflows.
• Experience with Docker, Kubernetes, or serverless architectures is a plus.
• Ability to think beyond deployment and consider operational reliability and long-term maintenance.

Data Handling

• Strong programming skills in Python.
• Proficiency in SQL and working with large-scale datasets.
• Ability to reason about data quality, data limitations, and how they impact ML outcomes.
• Familiarity with distributed computing frameworks like Spark or Dask is a plus.

Leadership and Communication

• Ability to lead and mentor ML Engineers and work effectively across teams.
• Strong communication skills to explain ML concepts, decisions, and limitations to business teams.
• Comfortable taking ownership and making decisions in ambiguous problem spaces.
• Passion for staying updated with advancements in ML and AI, with a practical mindset toward adoption.

Experience Needed

• 6+ years of experience in machine learning engineering or related roles.
• Proven experience designing, selecting, and deploying ML solutions used in production.
• Experience managing ML systems after deployment, including monitoring and iteration.
• Proven track record of working in cross-functional teams and leading ML initiatives.

Responsibilities 

Design, implementation and delivery of solutions.

Solving new problems and address any issues regarding the architecture and performance. 

Focused on understanding customer needs and anticipate the changing business and technology landscape. 

Collaborate with teams from various verticals within and outside the company.

Qualifications 

2-5 years of Software Engineering experience in Node.js and React. 

Proven experience in architecting performant, complex application on web or mobile applications. 

Knowledge of end to end Software development life cycle.

Ability to work individually or in teams and mentor new developers to the team.

Strong knowledge of computer science, algorithms and design patterns. 

A degree in Computer Science or related field, or equivalent industry experience.

MERN Stack Developer will work closely with the cross-team to discover effective and elegant solutions to complex problems.

·         Excellent knowledge of HTML, CSS, Material-UI and Responsive.

·         Strong concepts of Javascript, ReactJs, NextJS.

·         Should have Excellent Experience of Node.js.

·         In-Depth knowledge of Express Js, JavaScript, TypeScript,

·         Should have experience in MongoDB, My SQL, GraphQL, and any graph Database

·         Experience working with REST APIs, and Sockets.

·         Ability to Identify and fix production and non-production application issues as a part of the deployment.

·         Good Knowledge of AWS - Beanstalk, Cloud Watch.

·         Good Knowledge of JSON, API, and JWT.

·         Good to have Agile/JIRA/ Continuous Deployment experience.

·         Ability and willingness to manage multiple projects/tasks.

Job Responsibilities:

·         Should have completed B. Tech in IT / CS.

·         Understanding accessibility and security compliance (Depending on the specific project)

·         Understanding fundamental design principles behind a scalable application.

·         Good communication and language skills.

·         Strong focus on performance optimizations, caching, and scalability.

·         Ability to deal well with ambiguous/undefined problems; ability to think abstractly

Expi with Node.js, Express, Feather JS
3rd party API integration knowledge
Database- MySql or NoSql

Kafka Client Integration with Nodejs

Redis integration using Nodejs

• Serves customers by providing product and service information and resolving product and service problems.
• Attracts potential customers by answering product and service questions and suggesting information about other products and services.
• Opens customer accounts by recording account information.
• Maintains customer records by updating account information.
• Resolves product or service problems by clarifying the customer’s complaint, determining the cause of the problem, selecting and explaining the best solution to solve the problem, expediting correction or adjustment, and following up to ensure resolution.
• Maintains financial accounts by processing customer adjustments.
• Recommends potential products or services to management by collecting customer information and analyzing customer needs.
• Prepares product or service reports by collecting and analyzing customer information.
• Contributes to team effort by accomplishing related results as needed.

Skills Required 

• Customer service
• Product knowledge
• Market knowledge
• Quality focus
• Problem-solving
• Documentation skills
• Phone skills
• Listening
• Resolving conflict
• Analyzing information
• Multi-tasking
• communication 
• Fluent English