Machine Learning Engineer
Job Description
Job Title: Machine Learning Engineer
Company: MHTECHIN
Location: Pune, Maharashtra, India (Hybrid/Remote)
Employment Type: Full-time
Experience Required: 2–6 years
Salary Range: 12,00,000 – 24,00,000 per year
Education: Bachelor's in Computer Science, AI, Electrical Engineering, or equivalent experience
About MHTECHIN
MHTECHIN is building practical AI that powers products in fintech, agri-tech, and SME enablement. As a Machine Learning Engineer, you will design, train, and deploy models that go directly into production—owning the full lifecycle from experimentation to monitoring.
Key Responsibilities
Email your resume to [Confidential Information]
Job Category: Data Science
Job Type: Full Time
Job Location: Pune
Company: MHTECHIN
Location: Pune, Maharashtra, India (Hybrid/Remote)
Employment Type: Full-time
Experience Required: 2–6 years
Salary Range: 12,00,000 – 24,00,000 per year
Education: Bachelor's in Computer Science, AI, Electrical Engineering, or equivalent experience
About MHTECHIN
MHTECHIN is building practical AI that powers products in fintech, agri-tech, and SME enablement. As a Machine Learning Engineer, you will design, train, and deploy models that go directly into production—owning the full lifecycle from experimentation to monitoring.
Key Responsibilities
- Translate business problems into data/ML solutions with clear metrics and success criteria.
- Explore, clean, and prepare datasets; build features and baselines; run reproducible experiments.
- Train, evaluate, and optimize supervised, unsupervised, and deep learning models.
- Build robust data/ML pipelines for ETL, training, and real-time/batch inference.
- Deploy models using MLOps best practices including CI/CD, model registry, and monitoring.
- Collaborate with product and engineering teams to integrate models into APIs and applications.
- 2–6 years of hands-on experience in ML/DS/ML engineering with production deployments.
- Strong Python skills with experience in NumPy, Pandas, scikit-learn, and at least one deep learning framework (PyTorch or TensorFlow).
- Cloud deployment experience (AWS/GCP/Azure), containerization with Docker, and Git-based CI/CD.
- Strong SQL skills and understanding of data modeling.
- Ability to write clean, maintainable, and tested code.
- Experience with feature stores, workflow orchestration tools (Airflow/Prefect), and model monitoring.
- Knowledge of NLP (transformers), time-series modeling, or recommendation systems.
- Familiarity with FastAPI/Flask, streaming systems (Kafka/PubSub), or vector databases.
- Awareness of data security, privacy, and compliance standards.
- Impact: Your models will be used by real customers across India.
- Growth: Small, fast-moving team with high ownership and mentorship.
- Flexibility: Hybrid/remote-friendly with modern tooling and cloud stack.
- Competitive salary and performance bonuses.
- Health insurance and paid time off.
- Learning and development stipend.
- Modern hardware and remote working support.
Email your resume to [Confidential Information]
Job Category: Data Science
Job Type: Full Time
Job Location: Pune
More Info
About Company
Skills:
Power Bi, Tableau, Sql, Azure ML, Git, Databricks, Deployment Tracking, MLflow, MLOps processes and tools, Lineage, Production support practices, versioning, Model Registry, Reproducibility, Telecommunications environment, Cloud ML platforms, Monitoring
Skills:
data engineering , Machine Learning, Tensorflow, Pytorch, Docker, XGBoost, Python, AWS, Sql, Git, MLops, Azure, Feature Engineering, ML Pipelines, Model Evaluation, CI CD, Scikit-Learn, LangGraph, Model Deployment, ML Modelling, LangChain, CrewAI, LightGBM, AutoGen, Agentic AI
Skills:
Deep Learning, Git, Computer Vision, Python, real-time video streams, model optimization techniques, data preparation or processing pipelines, large-scale image and video datasets
Skills:
Docker, Pyspark, Pytest, Azure Databricks, Azure Cloud Services, Python, Sql, MLflow
Skills:
Spark, Java, Hadoop, Cloudformation, Yarn, Tensorflow, Hive, MLops, Docker, Sns, Python, Kubernetes, AWS, Airflow, Pipelines, H2O, EventBridge, CodeBuild, SageMaker, CodePipeline, CodeCommit, CloudTrail