Tile : MLE (Machine Learning Engineer)
Location: Pune
Experience: 8+ years
India
Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can, and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.
ABOUT CAPCO
Capco is a global technology and business consultancy, focused on the financial services sector. We are passionate about helping our clients succeed in an ever-changing industry. You will work on engaging projects with some of the largest banks in the world, on projects that will transform the financial services industry.
Key Responsibility
- Strong understanding of LLM architectures and expertise in fine tuning pre trained models on domain specific data.
- Experience with RAG, Prompt Engineering concepts and fundamentals (Vector DBs).
- Experience with containerization and orchestration technologies (Kubernetes, Docker).
- In depth knowledge of machine learning, deep learning, and NLP.
- Manage prioritization and technology work for building NLP, ML & AI solutions experience in experimenting and developing with LLM.
- Strong understanding of NLP techniques and framework such as BERT,GPT or Transformer models.
- Create and manage best practices for ML models integration, orchestration, and deployment, that will ensure secure including data versioning, ingress and model output egress, CI/CD pipelines for MLOps and LLMOps.
- Solid understanding of Machine learning concept and algorithm including supervised and unsupervised learning, model evaluation and deployment strategies in production environment.
- Follow AI best practices, ensuring fairness, transparency and accountability in AI model and system.
Skills Required | Qualification
- At least 8-10 years of experience in deploying end to end data science focused solutions.
- Should be strong technical background e.g. B.Tech /M.Tech from top tier institutes.
- Expertise in training and fine tune LLMs using popular framework such as (TensorFlow, PyTorch or hugging face transformer) and deployment tools (e.g. Docker, Kubeflow)
- Good exposure in Python.
- Knowledge in SQL, Pandas or Pyspark.
- Good to have understanding knowledge on GitHub, Confluence and JIRA
- Cloud Platforms knowledge have to: Azure /GCP
- Experience of senior stakeholder management and strong communication/presentation skills
- Excellent verbal and written communication skills.
- Present technical solutions, capabilities, considerations, and features in business terms.
WHY JOIN CAPCO?
You will work on engaging projects with some of the largest banks in the world, on projects that will transform the financial services industry.
We offer:
A work culture focused on innovation and building lasting value for our clients and employees
Ongoing learning opportunities to help you acquire new skills or deepen existing expertise
A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients
A diverse, inclusive, meritocratic culture
Enhanced and competitive family friendly benefits, including maternity / adoption / shared parental leave and paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement
NEXT STEPS
If you’re looking forward to progressing your career with us, please do not hesitate to apply. We are looking forward to receiving your application.
To learn more about Capco and its people check out the website on www.capco.com
