Weassistleading companies in designing, developing, andoperatingthe products and services that will define tomorrow's world.Wespecializeinenvisioning, designing,engineering, and managing digital goods and experiences for high-growth organizations striving to disrupt through innovation and velocity. Our experience helps businesses in fast-growing areas including Hi-tech, manufacturing, banking & financial services, insurance, consumer services, public services, and healthcare to achieve their goals.
Our USPs
Digital Innovation
Passionate Approach
Transparent Business Model
Job Overview:
We seek an experienced AIML Engineer with Python, PyTorch, TensorFlow, and Large Language Models (LLMs) expertise. The ideal candidate should have 3-4 years of focused experience in AI/ML and at least 6+ years of total experience in software engineering. The role involves designing, developing, and deploying machine learning models and solutions that address complex business challenges.
Key Responsibilities:
Model Development: Design and implement machine learning models using PyTorch and TensorFlow, focusing on Large Language Models (LLMs) and other advanced architectures.
Data Processing & Feature Engineering: Work with large datasets to preprocess, clean, and organize data for model training and testing, ensuring data quality and relevance.
Model Training & Optimization: Train, fine-tune, and optimize machine learning models for performance, scalability, and accuracy. Ensure models are production-ready and meet business objectives.
Model Evaluation: Conduct rigorous evaluation and validation of models, using appropriate metrics to assess model accuracy, precision, recall, and other KPIs.
Deployment & Scaling: Deploy models into production environments, utilizing tools and frameworks for continuous integration, scaling, and monitoring.
Research & Innovation: Stay updated with the latest advancements in AI/ML, especially in LLMs, and apply innovative techniques to enhance model effectiveness.
Cross-functional Collaboration: Work closely with data engineers, product managers, and software engineers to integrate machine learning solutions with existing applications and systems.
Documentation: Maintain clear, detailed documentation for models, code, and workflows to support reproducibility and knowledge sharing.
Required Skills:
Programming: Proficiency in Python, with experience in writing efficient, production-grade code.
Machine Learning Frameworks: Extensive experience with PyTorch and TensorFlow for building and deploying machine learning models.
Large Language Models (LLMs): Familiarity with LLMs, including architectures, training methodologies, fine-tuning, and application scenarios.
Data Manipulation & Analysis: Strong skills in data processing libraries (e.g., Pandas, NumPy) and experience working with large datasets.
Model Deployment: Knowledge of deploying ML models into production environments, with experience in containerization tools (e.g., Docker) and cloud platforms (e.g., AWS, GCP, Azure).
Algorithmic Knowledge: Understanding of machine learning algorithms, deep learning architectures, and NLP concepts.
Version Control: Proficiency in version control tools (e.g., Git) and experience with collaborative development workflows.
Communication: Strong verbal and written communication skills to effectively convey technical information to non-technical stakeholders.
Preferred Skills
Cloud Platforms: Experience with cloud services specific to AI/ML (e.g., AWS SageMaker, GCP AI Platform, Azure Machine Learning).
MLOps: Familiarity with MLOps practices, including CI/CD pipelines for ML, automated retraining, and monitoring.
Natural Language Processing (NLP): Background in NLP techniques, especially relevant for working with LLMs.
Visualization Tools: Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly) for data exploration and result presentation.
Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark) is a plus.
Qualifications
Bachelor’s or Master’s Degree in Computer Science, Data Science, AI/ML, or a related field.
Certifications or courses in AI/ML, deep learning, or related technologies are advantageous. Role & responsibilities
