Machine Learning Engineer

4 weeks ago

Thiruvananthapuram, Kerala, India ShellSquare Softwares Full time
Job Description

About The Role

We are looking for a skilled and motivated Machine Learning Engineer / Data Scientist

to join our team. The ideal candidate should have a strong foundation in machine

learning and deep learning, with experience in building end-to-end ML pipelines and

hybrid modeling approaches that incorporate both physics-based simulations and

data-driven insights. You will work on high-impact projects involving time series

forecasting, predictive modeling, and system simulation to support data-driven

decision-making.

Key Responsibilities

Design, train, and evaluate machine learning and deep learning models for

regression, classification, and forecasting tasks.

Build and maintain end-to-end ML pipelines, including data ingestion,

preprocessing, feature engineering, model training, validation, and deployment.

Develop physics-informed or hybrid models by combining domain knowledge

with machine learning approaches to simulate and predict system behaviors.

Implement and optimize time series forecasting models using statistical

techniques, classical ML, and deep learning architectures (e.g., LSTM,

Transformer).

Collaborate with cross-functional teams to transtranslate business needs into

machine learning solutions.

Monitor and refine model performance post-deployment to ensure robust,

scalable outcomes.

Key Skills Required

Strong knowledge of Machine Learning and Deep Learning algorithms and their

applications.

Proven experience in building and deploying end-to-end ML pipelines.

Hands-on experience in physics-based modeling or hybrid approaches

combining physical models with data-driven techniques.

Solid understanding of time series forecasting using statistical (ARIMA, ETS),

machine learning (XGBoost, RF), and deep learning (RNN, LSTM, Temporal CNN)

methods.

Experience designing regression and classification models for real-world

problems.

Proficiency in Python, and libraries like TensorFlow / PyTorch, scikit-learn,

pandas, NumPy, statsmodels, etc.

Strong problem-solving mindset and ability to work with minimal supervision.

Skills: deep learning,model training,statistical techniques,pytorch,scikit-learn,physics-based modeling,end-to-end ml pipelines,machine learning,feature engineering,time series forecasting,tensorflow,python,numpy,hybrid modeling,classification,pandas,deployment,preprocessing,time series analysis,statsmodels,regression,validation,data ingestion

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