Role Overview
We are looking for a Senior AI / Machine Learning Engineer with strong hands-on experience in classical
machine learning, advanced algorithms, and Reinforcement Learning (RL). The ideal candidate should
have worked on real-world ML projects, understand time-series and signal processing concepts, and
have exposure to wavelet analysis.
This role involves building, optimizing, and deploying intelligent models for complex, data-driven
systems. You will work closely with product, data, and engineering teams to design scalable AI solutions.
Key Responsibilities
Machine Learning & Modeling
Design, train, and optimize machine learning models using supervised, unsupervised, and semi-
supervised techniques
Implement and tune algorithms such as:
Linear & Logistic Regression
Decision Trees, Random Forests
Gradient Boosting (XGBoost, LightGBM, CatBoost)
SVM, KNN, Naive Bayes
Clustering (K-Means, DBSCAN, Hierarchical)
Perform feature engineering, data preprocessing, and model evaluation
Reinforcement Learning (Mandatory)
Design and implement RL agents for sequential decision-making problems
Work with RL algorithms such as:
Q-Learning, SARSA
DQN, Double DQN
Policy Gradient, Actor-Critic
PPO, A2C/A3C (preferred)
Define reward functions, state spaces, and action policies
Optimize agents for stability, convergence, and real-world constraints
Wavelet & Signal Analysis
Apply wavelet analysis for time-series decomposition and feature extraction
Use wavelets to detect patterns, anomalies, trends, or regime changes
Integrate wavelet-based features into ML/RL pipelines
Data & Deployment
Work with large datasets and time-series data
Build end-to-end ML pipelines from data ingestion to deployment
Collaborate on model deployment using APIs or production systems
Monitor model performance and improve accuracy over time
Required Skills & Qualifications
5+ years of experience in Machine Learning / AI
Strong command over ML fundamentals and algorithms
Proven hands-on experience with Reinforcement Learning
Practical experience with wavelet analysis or signal processing
Proficiency in Python and ML libraries (NumPy, Pandas, Scikit-learn, etc.)
Experience working on real-world ML projects (not just academic)
Strong understanding of mathematics, statistics, and probability
Ability to write clean, optimized, and well-documented code
Good to Have
Experience with deep learning frameworks (TensorFlow / PyTorch)
Experience with time-series forecasting or financial data
Knowledge of model deployment, APIs, or production ML systems
Research-oriented mindset with problem-solving skills
Work on advanced AI & RL-driven systems
Exposure to real-world, high-impact ML use cases
Collaborative and growth-oriented work environment
Long-term career growth with leadership opportunities
#JobOpening #Hiring #JobSearch #NowHiring #CareerOpportunity #Employment #JobOpportunity #JobListing #JobPosting #JobAlert #recruitmentIf interested can forward your updated resumes on hr5@tasolutions.in and can directly contact us on 9041287949 also can provide our reference to your friends and colleagues.
