telle caller

Role & Responsibilities

• Develop and deliver automation software to build and improve platform functionality
• Ensure reliability, availability, and manageability of applications and cloud platforms
• Champion adoption of Infrastructure as Code (IaC) practices
• Design and build self-service, self-healing, monitoring, and alerting platforms
• Automate development and testing workflows through CI/CD pipelines (Git, Jenkins, SonarQube, Artifactory, Docker containers)
• Build and manage container hosting platforms using Kubernetes

Requirements

• Strong experience deploying and maintaining GCP cloud infrastructure
• Well-versed in service-oriented and cloud-based architecture design patterns
• Knowledge of cloud services including compute, storage, networking, messaging, and automation tools (e.g., CloudFormation/Terraform equivalents)
• Experience with relational and NoSQL databases (Postgres, Cassandra)
• Hands-on experience with automation/configuration tools (Puppet, Chef, Ansible, Terraform)

Additional Skills

• Strong Linux system administration and troubleshooting skills
• Programming/scripting exposure (Bash, Python, Core Java, or Scala)
• CI/CD pipeline experience (Jenkins, Git, Maven, etc.)
• Experience integrating solutions in multi-region environments
• Familiarity with Agile/Scrum/DevOps methodologies

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.

Roles and Responsibilities:

1. Support Cybersecurity Assessments:

o Assist in conducting cybersecurity governance risk assessments for

applications.

o Help in the preparation and review of the Cybersecurity Governance

Assessment Questionnaire (CGAQ).

o Ensure all necessary information is collected and documented accurately.

o Provide guidance and support to ensure understanding and compliance with

cybersecurity requirements.

2. Issue and Exception Management:

o Track and follow up on issues and exceptions identified during assessments.

o Ensure timely closure of findings from assessments and audits.

o Document and report the status of issues and exceptions to relevant

stakeholders.

3. Documentation and Reporting:

o Assist in maintaining accurate records of assessments, issues, and exceptions.

o Maintain contact with with IT and Business to ensure customer satisfaction

Required experience:

• Minimum 1 year of experience in Web & Backend Development using Python

Overview

We are looking for Python developers with a strong understanding of object orientation and experience in web and backend development. Experience with Analytical algorithms and mathematical calculations using libraries such as Numpy and Pandas are a must. Experience in some form of Machine Learning. We require candidates who have working experience using Django Framework

Key Skills required (Items in Bold are mandatory keywords) :

1. Proficiency in Python 3.x based web and backend development
2. Solid understanding of Python concepts
3. Experience with some form of Machine Learning (ML)
4. Experience in using libraries such as Numpy and Pandas
5. Some form of experience with NLP and Deep Learning using any of Pytorch, Tensorflow, Keras, Scikit-learn or similar
6. Hands on experience with RDBMS such as Postgres or MySQL
7. Experience building REST APIs using DRF or Flask
8. Comfort with Git repositories, branching and deployment using Git
9. Working experience with Docker
10. Basic working knowledge of ReactJs
11. Experience in deploying Django applications to AWS,Digital Ocean or Heroku

Lead DevSecOps Engineer

Location: Pune, India (In-office) | Experience: 3–5 years | Type: Full-time

Apply here → https://lnk.ink/CLqe2

About FlytBase:

FlytBase is a Physical AI platform powering autonomous drones and robots across industrial sites. Our software enables 24/7 operations in critical infrastructure like solar farms, ports, oil refineries, and more.

We're building intelligent autonomy — not just automation — and security is core to that vision.

What You’ll Own

You’ll be leading and building the backbone of our AI-native drone orchestration platform — used by global industrial giants for autonomous operations.

Expect to:

• Design and manage multi-region, multi-cloud infrastructure (AWS, Kubernetes, Terraform, Docker)
• Own infrastructure provisioning through GitOps, Ansible, Helm, and IaC
• Set up observability stacks (Prometheus, Grafana) and write custom alerting rules
• Build for Zero Trust security — logs, secrets, audits, access policies
• Lead incident response, postmortems, and playbooks to reduce MTTR
• Automate and secure CI/CD pipelines with SAST, DAST, image hardening
• Script your way out of toil using Python, Bash, or LLM-based agents
• Work alongside dev, platform, and product teams to ship secure, scalable systems

What We’re Looking For:

You’ve probably done a lot of this already:

• 3–5+ years in DevOps / DevSecOps for high-availability SaaS or product infra
• Hands-on with Kubernetes, Terraform, Docker, and cloud-native tooling
• Strong in Linux internals, OS hardening, and network security
• Built and owned CI/CD pipelines, IaC, and automated releases
• Written scripts (Python/Bash) that saved your team hours
• Familiar with SOC 2, ISO 27001, threat detection, and compliance work

Bonus if you’ve:

• Played with LLMs or AI agents to streamline ops and Built bots that monitor, patch, or auto-deploy.

What It Means to Be a Flyter

• AI-native instincts: You don’t just use AI — you think in it. Your terminal window has a co-pilot.
• Ownership without oversight: You own outcomes, not tasks. No one micromanages you here.
• Joy in complexity: Security + infra + scale = your happy place.
• Radical candor: You give and receive sharp feedback early — and grow faster because of it.
• Loops over lines: we prioritize continuous feedback, iteration, and learning over one-way execution or rigid, linear planning.
• H3: Happy. Healthy. High-Performing. We believe long-term performance stems from an environment where you feel emotionally fulfilled, physically well, and deeply motivated.
• Systems > Heroics: We value well-designed, repeatable systems over last-minute firefighting or one-off effort.

Perks:

▪ Unlimited leave & flexible hours

▪ Top-tier health coverage

▪ Budget for AI tools, courses

▪ International deployments

▪ ESOPs and high-agency team culture

Apply Here- https://lnk.ink/CLqe2

Job Title: E-Commerce Executive

Salary: ₹16,000 - ₹25,000 per month

Experience: Minimum 1 year in e-commerce

Job Description:

We are seeking a motivated and detail-oriented E-Commerce Executive to join our dynamic team. The ideal candidate will have a solid understanding of e-commerce platforms, particularly Amazon, and will be responsible for managing and optimizing our online sales channels.

Key Responsibilities:

- Manage and optimize product listings on Amazon and other e-commerce platforms.

- Monitor inventory levels and coordinate with suppliers to ensure timely stock replenishment.

- Analyze sales data and market trends to identify opportunities for growth.

- Implement marketing strategies to enhance product visibility and drive sales.

- Handle customer inquiries and resolve issues related to online orders.

- Collaborate with the marketing team to create promotional campaigns.

- Stay updated on e-commerce trends and best practices.

Qualifications:

- Minimum 1 year of experience in e-commerce management.

- Knowledge of Amazon Seller Central and other e-commerce platforms.

- Strong analytical skills and attention to detail.

- Excellent communication and interpersonal skills.

- Ability to work independently and as part of a team.

- Proficiency in Microsoft Office and e-commerce management tools.

• Contributing to the backend of the product development.
• Maintaining these applications for accuracy and high availability.
• Contributing to and enforcing great coding practices through code reviews.
• Sharing knowledge with your colleagues during regular knowledge Sharing sessions.
• Collaborate across functions and own the planning, estimation and execution for parts of the product.
• Continuously identify opportunities to improve system designs, architecture and implementation standards.

• Experience of architecting and building products/business critical backend applications using Ruby on Rails.
• Experience with relational databases like Postgres or MySQL.
• Experience of deploying and maintaining web applications.
• Exposure to cloud infrastructure like AWS, GCP etc.
• Familiarity with REST APIs and stress testing tools.
• Good communication skills.