About Us At Acompworld, we are trusted technology partners to leading enterprises, transforming their most complex challenges into scalable, intelligent, and secure software solutions. We are looking for a seasoned Senior Full Stack Engineer who is passionate about building high-impact products and thrives in a client-facing, collaborative environment. Key Responsibilities Solution Architecture: Lead the design, development, and deployment of sophisticated, secure, and scalable applications using modern front-end and back-end technologies. AI-Powered Innovation: Integrate and leverage AI/ML services (e.g., OpenAI, Azure AI, Google Vertex AI) to build intelligent features and automate business processes for our enterprise clients. Cloud & DevOps: Architect and manage robust solutions on AWS, Azure, or GCP. Champion a strong DevOps culture by building and maintaining automated CI/CD pipelines using Infrastructure as Code (IaC), Docker, and Kubernetes. Observability & Performance: Implement and manage monitoring, logging, and alerting solutions (e.g., using Datadog, Prometheus, Grafana, ELK Stack) to ensure high availability and performance of production systems. Data-Driven Systems: Design and implement solutions that involve complex data models and integrate with large-scale databases and data pipelines. Client Partnership: Collaborate directly with enterprise stakeholders to translate complex business requirements into detailed technical specifications, lead solution demos, and iteratively refine products based on feedback. Team Mentorship & Quality Advocacy: Mentor junior engineers, conduct rigorous code reviews, and enforce best practices in testing, security (OWASP Top 10), and accessibility (WCAG/ADA) to ensure enterprise-grade quality. Required Skills & Experience Frontend: Expert proficiency in at least one modern framework (React, Angular, or Vue) with TypeScript. Deep understanding of state management (e.g., Redux, Zustand, NgRx), modern CSS, and building responsive, accessible UIs. Backend: Proven experience with one or more server-side languages (Node.js, Python, .NET Core, Java), including designing and building secure RESTful and/or GraphQL APIs. Databases: Advanced proficiency with both SQL (e.g., PostgreSQL, SQL Server) and NoSQL (e.g., MongoDB, DynamoDB, Cosmos DB) databases, including data modeling and performance tuning. Cloud Platform: Demonstrable experience deploying and managing production applications on AWS, Azure, or GCP (including serverless, containers, IAM, and networking). DevOps: Hands-on experience with CI/CD tools (e.g., GitHub Actions, Jenkins, Azure DevOps). Strong knowledge of Docker and container orchestration with Kubernetes. Architecture & Integration: Solid understanding of microservices and event-driven architecture. Proven experience integrating with enterprise systems (e.g., SAP, Salesforce, Oracle) and third-party services (e.g., Auth0, Stripe). Soft Skills: Exceptional communication, problem-solving, and leadership skills. Ability to work autonomously and translate ambiguous client needs into concrete technical solutions. Nice-to-Have Skills Experience within a specific enterprise domain (e.g., Energy, Manufacturing, Supply Chain, Healthcare). Relevant cloud certifications (e.g., AWS Certified Solutions Architect, Azure Developer Associate). Experience with data visualization libraries or tools (e.g., D3.js, Power BI, Tableau).
We are looking for a skilled Deep Learning Engineer with strong expertise in object detection and segmentation model development. The ideal candidate should have hands-on experience with deep learning frameworks, data preparation, and model deployment on various environments, including Docker and Linux/Windows systems. This role involves both applied implementation and research-driven development of computer vision models for real-world applications. Key Responsibilities: 1. Object Detection & Segmentation: Hands-on experience in implementing and fine-tuning object detection models such as YOLOvX, EfficientDet, Faster R-CNN, SSD, and Mask R-CNN. Work on real-time object detection use cases with performance optimization. 2. Programming & Frameworks: Strong programming experience in Python. Proficiency in deep learning frameworks such as TensorFlow, PyTorch, OpenCV, and ONNX. 3. Data Preparation & Annotation: Expertise in dataset creation, annotation, augmentation, and preprocessing. Experience with tools like Roboflow, CVAT, LabelImg, and similar annotation platforms. 4. Model Research & Development: Ability to understand and implement state-of-the-art research papers. Participate in R&D activities to improve model accuracy, efficiency, and robustness. 5. System & Deployment Experience: Proficient with Linux and Windows operating systems for model development and deployment. Experience with Docker for containerizing ML models and setting up reproducible environments. Familiarity with model deployment practices for local, cloud, or edge systems. 6. Collaboration & Documentation: Work closely with cross-functional teams including data engineers, software developers, and product managers. Document code, experiments, results, and deployment procedures. Preferred Experience & Skills: 2+ years of hands-on experience in deep learning, particularly in computer vision and object detection. Exposure to model optimization techniques (e.g., quantization, pruning). Knowledge of deployment pipelines using Docker, and optionally Kubernetes. Experience with edge deployment on devices like NVIDIA Jetson or using frameworks like TensorRT/OpenVINO. Strong problem-solving skills and the ability to work independently and collaboratively in a team environment. Familiarity with experiment tracking tools (e.g., MLflow, Weights & Biases) is a plus.
We are looking for a detail-oriented and analytical Software Test Engineer to join our dynamic team. You will be responsible for ensuring our software is robust, reliable, and meets the highest standards before it reaches our users. This role requires a passion for quality, a knack for breaking things, and a commitment to continuous improvement in a fast-paced, agile environment. Responsibilities Test Planning & Strategy: Design and develop comprehensive test plans and test cases based on product requirements and technical specifications. Manual & Automated Testing: Execute manual and automated tests across various platforms (web, mobile) to identify, document, and track defects from discovery to resolution using tools like Jira. Automation Development: Develop, maintain, and enhance automated test scripts and frameworks using tools like Selenium, Cypress, or Playwright to improve testing efficiency and coverage. Performance & Load Testing: Plan and execute non-functional tests to ensure system performance, stability, and scalability under load. Security Testing: Perform baseline security testing to identify common vulnerabilities (such as OWASP Top 10) and work with the development team to ensure remediation. Reporting & Analysis: Create detailed and understandable bug reports and test summary reports to communicate testing progress and product quality to stakeholders. Skills & experience Strong understanding of STLC, SDLC, and various testing methodologies (e.g., Agile, Scrum). Proven experience in writing clear, concise, and comprehensive test plans and test cases. Hands-on experience with automated testing tools such as Selenium , Cypress , or Playwright . Solid knowledge of at least one programming/scripting language, preferably Python or Java . Knowledge of common security vulnerabilities (e.g., OWASP Top 10) and basic security testing principles. Experience with API testing tools like Postman or Rest-Assured . Familiarity with bug tracking and project management tools like Jira or Azure DevOps . Excellent problem-solving skills and a keen eye for detail. Strong verbal and written communication skills ; able to articulate complex issues to both technical and non-technical team members. Nice-to-have Experience with performance and load testing tools such as JMeter or LoadRunner . Knowledge of CI/CD pipelines and experience integrating automated tests using tools like Jenkins or GitHub Actions . Familiarity with testing on cloud platforms ( AWS , Azure , or GCP ). Exposure to security testing principles and tools. Understanding of database concepts and experience with SQL .