Talworx is an emerging recruitment consulting and services firm, we are hiring for our client which is a global financial service leader and provides governments, businesses, and individuals with market data, expertise, and technology solutions for confident decision-making. Our services span from global energy solutions to sustainable finance solutions. From helping our customers perform investment analysis to guiding them through sustainability and energy transition across supply chains, our solutions help unlock new opportunities and solve challenges.
What’s in it for you:
- Be a part of a global company and build solutions at enterprise scale
- Work with a highly skilled and hands-on technical team (including leadership)
- Contribute to solving high complexity, high impact problems
- Build and maintain production ready pipelines from ideation to deployment
Responsibilities:
- Design, build, and deploy scalable machine learning models for information extraction and natural language processing.
- Develop end-to-end ML pipelines, from data preprocessing and feature engineering to model training, evaluation, and deployment.
- Work with large-scale data processing frameworks like Apache Spark to build efficient and optimized ML solutions.
- Optimize ML models for performance, accuracy, and scalability in production environments.
- Develop and maintain streaming and batch data transformation pipelines using cloud-native solutions (AWS/GCP).
- Implement best practices in MLOps, including CI/CD pipelines for ML models, automated testing, and model monitoring.
- Deploy and manage containerized ML applications using Docker and Kubernetes.
- Collaborate closely with data engineers, software developers, and product teams to integrate ML solutions into enterprise workflows.
- Stay up to date with emerging trends in machine learning, NLP, and AI, applying new techniques to improve existing models.
- Ensure high code quality, performance, and adherence to best practices for software development.
What We’re Looking For:
- 5-8 years of experience in Machine Learning, NLP, and MLOps or related technology.
- Strong expertise in Python and ML/NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face).
- Experience with LangChain for LLM-based applications (retrieval-augmented generation, prompt engineering, and AI-driven search).
- Experience working with distributed computing frameworks such as Apache Spark for large-scale data processing.
- Hands-on experience in cloud-based ML development (AWS/GCP).
- Strong understanding of data preprocessing, feature engineering, model training, and evaluation.
- Experience with MLOps best practices, including automated model deployment and monitoring.
- Proficiency in SQL (any variant, big data experience is a plus).
- Familiarity with Linux OS (bash scripting, utilities, etc.).
- Version control experience with Git, GitHub, or Azure DevOps.
- Strong problem-solving, debugging, and optimization skills.
Nice to Have:
- Experience with Core Java 17+ (preferably Java 21+) and its toolchain.
- Knowledge of Apache Kafka and Apache Avro.
- Exposure to JVM-based languages such as Kotlin or Scala.
