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TSS Consultancy Pvt. Ltd.
Lead Software Engineer – AI
TSS Consultancy Pvt. Ltd.
Mumbai•On-site•5-8 Yrs•1 hour ago
Job description
Overview
Company Description
Responsibilities
- TSS Consultancy is a rapidly growing product-based company dedicated to delivering comprehensive solutions tailored to the unique needs of Fintech and Regtech organizations. Our mission is to fight financial crime through innovation and expertise. With a keen understanding of the market, we have developed cutting-edge products that set us apart in the industry.
- Our commitment to excellence has earned us the trust and partnership of some of the most prestigious institutions. We proudly serve 9 out of the top 10 brokers, 4 out of the top 5 private sector banks, and 3 out of the top 4 exchanges. Our client portfolio extends further, including leading financial institutions and regulatory bodies, reinforcing our reputation as a reliable and forward-thinking partner.
- We have our vibrant offices in the cities of Mumbai, Rajkot and Gandhinagar. In our growing presence we currently have our clients across India, South Africa and USA.
- The Opportunity:
- Lead the end-to-end lifecycle of AI-powered solutions, encompassing computer vision, NLP, and predictive modeling.
- Drive the development of innovative use cases in areas such as image enhancement, document intelligence, entity extraction, and automated data validation.
- Apply advanced deep learning techniques, transformer architectures, and foundation model fine-tuning to build scalable solutions for real-world applications.
- Design and architect robust and scalable AI services, seamlessly integrating them via REST APIs and microservices.
- Proactively explore and evaluate cutting-edge technologies in the AI landscape, including generative AI, multilingual AI, and biometric verification, to identify potential applications.
- Build and maintain robust CI/CD pipelines specifically tailored for model training, deployment, and rigorous testing.
- Implement comprehensive automation for model monitoring, retraining workflows, and ensure end-to-end traceability for both models and datasets.
- Leverage industry-standard MLOps tools such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes to facilitate production-grade deployment and management of AI systems.
- Lead the research, development, and proof-of-concept (PoC) efforts for domain-specific language models.
- Implement state-of-the-art transformer-based architectures to address complex NLP tasks, including text summarization, semantic search, and question-answering (QA) systems.
- Expertly fine-tune large language models (LLMs) to extract valuable insights from unstructured data sources.
- Strategically integrate NLP modules into core business workflows and real-time operational systems.
- Provide effective mentorship and guidance to a team of skilled machine learning engineers and software developers, fostering their professional growth.
- Collaborate closely with cross-functional stakeholders, including product managers and business analysts, to define product vision and contribute to the engineering roadmap.
- Take ownership of sprint planning, ensure timely and high-quality delivery of AI solutions, and conduct thorough code and architecture reviews.
Qualifications
- A minimum of 5 years of hands-on experience in AI/ML development, with demonstrable expertise in:
- Computer Vision: (e.g., Optical Character Recognition (OCR), Deepfake Detection)
- Natural Language Processing (NLP): (e.g., Text Parsing, Transformer Networks, GPT fine-tuning)
- Machine Learning Frameworks: PyTorch, TensorFlow, Hugging Face Transformers library
- MLOps Tools: MLflow, Kubeflow, Airflow, Docker, Kubernetes
- Strong proficiency in Python programming; familiarity with Java, Go, or Node.js is considered a plus.
- Solid understanding and practical experience with RESTful APIs and microservices architecture.
- Proven experience with DevOps tools and practices, including Jenkins, GitHub Actions, Prometheus, and Grafana.
- Demonstrated success in leading and managing teams of 5 to 10 engineers, fostering a collaborative and high-performing environment.
- Excellent communication skills, both written and verbal, with the ability to effectively convey complex technical concepts to both technical and non-technical audiences.
- Strong project management skills, with a track record of delivering AI projects on time and within scope.
- The ability to translate abstract product requirements into well-defined and scalable AI system architectures.
Nice to have
- Bachelor's or Master's degree (B.Tech/M.Tech) in Computer Science, Artificial Intelligence, or a related field.
- Exposure to and understanding of the specific requirements and challenges within the financial or other regulated domains.