1114 Machine Learning Engineer jobs in Hyderabad

Position: AI/ML Engineer

Experience: 4+ years

Location: Hyderabad- Hybrid

Notice Period: Immediate to 30 days joiners preferred

Job Overview:

Must have skills-

• Python : Experience with ML Libraries and at least 5 years of coding experience of building pipelines in Python/PySpark (libraries like NumPy, pandas, scikit-learn).
• Data preprocessing : Cleaning, transforming, and augmenting datasets to make them “ML-ready.” Experience with AWS GIS (Glue Interactive) and AWS Sagemaker
• Feature engineering : Identifying and creating relevant features that improve model accuracy and interpretability.
• Exploratory data analysis (EDA) : Using tools (matplotlib, seaborn, etc.) to visualize data and gain insights.

Full-Stack ML Engineer (Streamlit + Python)

Location: Remote / India

Experience: 4–6 years

Role Summary:

You will develop AI-powered tools using Streamlit for enterprise users—supporting use cases like spreadsheet summarization, HR Q&A bots, and performance engineering insight extraction.

Key Responsibilities:

• Build Streamlit apps for AI-assisted internal workflows
• Integrate frontend components with backend Python pipelines and vector stores
• Use LangChain or LlamaIndex to enable RAG with local LLMs
• Package apps using Docker for AWS deployment

Must-Have Skills:

• Python (Pandas, Scikit-learn, FastAPI or Flask)
• Experience with Streamlit or Dash for rapid UI development
• Familiarity with LLM APIs, Ollama, or Hugging Face models
• Vector DB integration (Chroma, FAISS, etc.)
• Bonus: Knowledge of HR/Performance engineering domains

We are seeking a highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team.

You will play a key role in designing, developing and productionalizing ML applications by evaluating models, training and/or fine tuning them. You will play a crucial role in developing Gen AI based solutions for our customers. As a senior member of the team, you will take ownership of projects, collaborating with engineers and stakeholders to ensure successful project delivery.

What we're looking for:

• At least 3 years of experience in designing & building AI applications for customer and deploying them into production
• At least 5 years of Software engineering experience in building Secure, scalable and performant applications for customers.
• Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.
• Design, develop, and operationalize existing ML models by fine tuning, personalizing it.
• Evaluate machine learning models and perform necessary tuning.
• Develop prompts that instruct LLM to generate relevant and accurate responses.
• Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.
• Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.
• Hands on customer experience with RAG solution or fine tuning of LLM model.
• Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.
• Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.
• Proven experience building and deploying machine learning models in production environments for real life applications
• Good understanding of natural language processing, computer vision or other deep learning techniques.
• Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
• Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
• Excellent communication, collaboration, and problem-solving skills.

Good to Have

• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.
• Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure.
• Experience with Amazon Lex or Google DialogFlow CX or Microsoft Copilot studio for CCAI Agent workflows
• Experience with AutoML and vision techniques.
• Master’s degree in statistics, machine learning or related fields.

Full-Stack ML Engineer (Streamlit + Python)

Location: Remote / India

Experience: 4–6 years

Role Summary:

You will develop AI-powered tools using Streamlit for enterprise users—supporting use cases like spreadsheet summarization, HR Q&A bots, and performance engineering insight extraction.

Key Responsibilities:

• Build Streamlit apps for AI-assisted internal workflows
• Integrate frontend components with backend Python pipelines and vector stores
• Use LangChain or LlamaIndex to enable RAG with local LLMs
• Package apps using Docker for AWS deployment

Must-Have Skills:

• Python (Pandas, Scikit-learn, FastAPI or Flask)
• Experience with Streamlit or Dash for rapid UI development
• Familiarity with LLM APIs, Ollama, or Hugging Face models
• Vector DB integration (Chroma, FAISS, etc.)
• Bonus: Knowledge of HR/Performance engineering domains

We are seeking a highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team.

You will play a key role in designing, developing and productionalizing ML applications by evaluating models, training and/or fine tuning them. You will play a crucial role in developing Gen AI based solutions for our customers. As a senior member of the team, you will take ownership of projects, collaborating with engineers and stakeholders to ensure successful project delivery.

What we're looking for:

• At least 3 years of experience in designing & building AI applications for customer and deploying them into production
• At least 5 years of Software engineering experience in building Secure, scalable and performant applications for customers.
• Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.
• Design, develop, and operationalize existing ML models by fine tuning, personalizing it.
• Evaluate machine learning models and perform necessary tuning.
• Develop prompts that instruct LLM to generate relevant and accurate responses.
• Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.
• Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.
• Hands on customer experience with RAG solution or fine tuning of LLM model.
• Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.
• Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.
• Proven experience building and deploying machine learning models in production environments for real life applications
• Good understanding of natural language processing, computer vision or other deep learning techniques.
• Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
• Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
• Excellent communication, collaboration, and problem-solving skills.

Good to Have

• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.
• Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure.
• Experience with Amazon Lex or Google DialogFlow CX or Microsoft Copilot studio for CCAI Agent workflows
• Experience with AutoML and vision techniques.
• Master’s degree in statistics, machine learning or related fields.

Position: AI/ML Engineer

Experience: 4+ years

Location: Hyderabad- Hybrid

Notice Period: Immediate to 30 days joiners preferred

Job Overview:

Must have skills-

• Python: Experience with ML Libraries and at least 5 years of coding experience of building pipelines in Python/PySpark (libraries like NumPy, pandas, scikit-learn).
• Data preprocessing: Cleaning, transforming, and augmenting datasets to make them “ML-ready.” Experience with AWS GIS (Glue Interactive) and AWS Sagemaker
• Feature engineering: Identifying and creating relevant features that improve model accuracy and interpretability.
• Exploratory data analysis (EDA): Using tools (matplotlib, seaborn, etc.) to visualize data and gain insights.

We seek a Machine Learning Engineer colleague to join our world-class client, one of thebiggest and most advanced IT company.• Remote work• Employment/Contract Type: Contract• Location: India• Duration: 1 year (with potential to be extended)• Hours per Week: 40 (Full-time)Description:We are seeking an experienced Machine Learning Engineer to join our growing team ofconsultants. In this role, you will be responsible for designing, developing, and deploying machinelearning models and algorithms to solve complex business challenges with Databricks. You will workclosely with data scientists, data engineers, and business stakeholders to build scalable and efficientmachine learning solutions.Key Responsibilities● Design and implement machine learning models and algorithms with Databricks, includingpredictive analytics, natural language processing, computer vision, and more.● Lead the end-to-end development process, from data collection and preprocessing to modeldeployment and monitoring.● Collaborate with cross-functional teams to understand business requirements and translatethem into technical solutions.● Optimize and fine-tune models for performance, accuracy, and scalability in a productionenvironment.● Stay up-to-date with the latest advancements in machine learning and AI, and apply them toimprove existing systems.● Contribute to the development of machine learning infrastructure, including data pipelines,model serving frameworks, and monitoring tools.● Collaborate with client stakeholders to drive solutions to solve business problems.Qualifications● Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a relatedfield; Ph D is a plus.● 3+ years of experience in machine learning engineering or related fields.● 2+ years of experience with Databricks● Proficiency in programming languages such as Python, R, or Java, with a strong understandingof machine learning libraries and frameworks (e.g., Tensor Flow, Py Torch, scikit-learn).● Experience with cloud platforms and MLOps tools, such as MLflow, for model deployment andmonitoring.● Strong problem-solving skills and ability to work in a fast-paced environment.● Excellent communication and collaboration skills, with a track record of working effectively incross-functional teamsAbout DexianDexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.

What You’ll DoCollaborate with research teams to prepare datasets for training and evaluation.Implement and run model training workflows, including hyperparameter tuning.Perform rigorous evaluation of models against benchmark datasets.Build and maintain pipelines for data preprocessing, feature extraction, and dataset versioning.Contribute to model deployment and monitoring in production environments.Who You Are2–5 years experience in machine learning engineering or applied data science.Strong programming skills in Python (Py Torch, Tensor Flow, or equivalent).Experience with data wrangling and large dataset preparation.Ability to collaborate closely with ML researchers on experimental workflows.Comfortable with cloud environments (AWS/GCP/Azure) and containerization (Docker).