Creative Synergies Group Overview:
- Creative is a leading global technology services firm delivering innovative solutions that synergise our deep engineering domain expertise and Digital Engineering Services
- Creative's global team of 1,600+ Can-Do engineers collaborate with our 40+ Fortune 500 clients to help them achieve their strategic and operational objectives (Including Google, Tesla, Samsung, Mercedes, Toyota, Mitsubishi, Hitachi)
- 95% of our revenues accrue from US, Europe, Japan based customers
- We work with clients across the global Transportation, Energy/Process, Industrial Products, Hi-Tech, Ed-Tech Industries.
Service Offerings:
Al/ML and Digital Technologies:
- Agentic AI
- GenAI Business Services
- AI/ML
- Data Analytics and Data Engineering
- Cloud Technologies
- Application Development
- Digital Platform Engineering
- Cybersecurity
Intelligent Connected Products:
- Edge Analytics
- Industrial and Consumer IoT
- Platform Development
- Mobile Robotics
- Vehicle Centric Electronics
- Connected Car and Telematics Solutions
Digital Manufacturing:
Digital Plant Engineering:
Founder / CEO: Dr. Mukesh Gandhi
- Former Michigan State University Professor(1984 - 1999)
- Published Ground-Breaking Technical Publications and Books Supervised PhD, Masters and Undergraduate Research Students - Who Are Now Leaders and Decision Makers in Industry and Academia
Awarded Over $15 Million For Pioneering Research from National Science Foundation (NSF), US Army Research Office (ARO), Defense Advanced Research Projects Agency (DARPA), US National Institute of Standards and Technology (NIST)
Founder / CEO of Quantech Global Services
- Pioneering US-Indian Services company to serve major global automotive OEMs (GM, Ford, Nissan, Peugeot) from India-based delivery centers in the early 2000s
- Acquired by Wipro (NYSE: WIT)
Former Wipro, EDS Chief Executive
Founded Creative Synergies Group In 2011
- Locations: Headquartered in the U.S., multiple delivery centers in India (Bengaluru, Pune, Noida), branch offices in Germany, U.K, Netherlands and Japan
- Culture: Creative has a flat organization and an agile culture of positivity, entrepreneurial spirit, customer centricity, teamwork, and meritocracy
Creative Synergies Group 3 Year Vision
- Continue Business Growth of 30-40% per annum
- Establish AI/ML Technology Services Leadership in Our Target Verticals
- Niche Technology Acquisitions in the U.S. / Europe
Job Overview:
We are seeking an experienced Senior Machine Learning Engineer (Computer Vision) with 5–10 years of experience in building, deploying, and optimizing ML and computer vision solutions at scale. The role focuses on developing end-to-end ML systems grounded in strong data science fundamentals, while increasingly integrating Gen AI capabilities such as RAG, multimodal models, and agent-based workflows.
The candidate will work closely with product, platform, and MLOps teams to design reliable, scalable ML components that move from experimentation to production, ensuring performance, accuracy, and long-term maintainability.
Key Responsibilities:
- Design, develop, and deploy computer vision and machine learning models for real-world business use cases.
- Apply strong data analysis, statistical reasoning, and feature engineering to improve model performance and robustness.
- Build and optimize deep learning models using CNNs and Transformer-based architectures for vision and multimodal tasks.
- Own the end-to-end ML lifecycle, including data preparation, training, evaluation, tuning, and production deployment.
- Collaborate with MLOps teams to support model versioning, monitoring, retraining, and performance tracking in production.
- Design ML components that integrate seamlessly into larger application and platform architectures.
- Contribute to GenAI initiatives, including building RAG pipelines that combine vision and text data, and integrating CV outputs into LLM workflows.
- Implement and evaluate single-agent and limited multi-agent workflows where applicable.
- Select appropriate evaluation metrics and clearly explain model trade-offs, limitations, and outcomes to stakeholders.
- Mentor junior engineers and contribute to knowledge sharing and best practices within the team.
- Collaborate closely with cross-functional teams including product, data, platform, and engineering to deliver end-to-end solutions.
Key Skills and Qualifications:
- Strong foundation in machine learning, deep learning, and data science principles, including supervised and unsupervised learning.
- Hands-on experience with computer vision models, including CNNs and Transformer-based architectures.
- Proficiency in Python and common ML/data libraries, with solid understanding of data structures and algorithms.
- Experience with SQL, data pre-processing, and feature engineering for structured and unstructured datasets.
- Practical experience deploying ML models into production environments and handling challenges such as data imbalance, drift, and noisy labels.
- Familiarity with cloud-based ML workflows on platforms such as AWS, Azure.
- Exposure to distributed training or large-scale data processing environments.
- Working knowledge of MLOps practices, including monitoring, retraining, and experiment tracking.
- Experience with GenAI concepts, including RAG systems, multimodal pipelines, lightweight fine-tuning, and evaluation of LLM outputs.
- Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Experience in Edge based deployment on AI models ex CoreML for iOS, and TensorFlow Lite (TFLite) for mobile deployment.
- Knowledge about Hardware Acceleration Experience with NVIDIA Jetson, Coral Edge TPU, or mobile NPUs (Neural Processing Units).
- Video Orchestration: GStreamer or FFmpeg for low-latency camera stream ingestion.
- Frameworks: PyTorch or TensorFlow; TorchVision for vision-specific primitives.
- Inference Optimization using NVIDIA TensorRT, OpenVINO, or TFLite for low-latency performance.
- Experience in sports domain will be a plus.
Educational Background:
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
- Advanced certifications such as AWS Certified Machine Learning – Specialty ,Microsoft Certified: Azure AI Engineer Associate are good to have.
- Specialized training in Machine Learning, AI, or Cloud ML platforms are a plus.
