122 Senior Product Manager AI Enterprise jobs in Vijayawada

Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.Key Responsibilities:Design and develop generative AI models using techniques like RAG, transformers, and other relevant approaches.Fine-tune pre-trained LLMs for specific tasks and domains.Conduct research on new techniques for improving the performance and capabilities of generative AI models.Apply software engineering rigor and best practices to machine learning /Generative AI pipelines.Evaluate and analyse the performance of ML/generative AI models.Stay up to date on the latest advancements in generative AI research.Facilitate the development and deployment of proof-of-concept Generative AI systems.Qualifications:Bachelor’s/Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.3-5 years of experience in generative AI or related fields.Experience in building data pipelines, deploying ML/Gen AI models in production, and monitoring and maintaining their performance.Strong programming skills in Python.Familiarity with RAG and other techniques for building generative models.Extensive experience with Git, Docker and a good understanding of Linux for managing servers.Experience with cloud-based ecosystems, especially AWS ML/Gen AI services.Exposure to ML/Gen AI frameworks and tools.Excellent communication and collaboration skills.Ability to work independently and in a team-oriented environment.Methodical and meticulous towards work and planning.

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).

Role Overview

You will design, optimize, and deploy real-time computer vision and machine learning pipelines for a multi-sensor biometric authentication device. This includes processing high-resolution data from RGB, IR, and depth/thermal sensors, implementing robust anti-spoofing mechanisms, and integrating privacy-preserving encrypted face-matching algorithms (e.g., CKKS/FHE). The role demands expertise in embedded GPU platforms (NVIDIA Jetson series) and the ability to push models to production under strict latency and security constraints.

Responsibilities

Model Development & Optimization

• Build and fine-tune face detection, alignment, and embedding extraction models for RGB + IR + depth + thermal data.
• Research and implement spoof detection (e.g., texture analysis, depth cues, challenge-response).
• Quantize and optimize models for Jetson hardware (TensorRT, ONNX Runtime, CUDA/CuDNN).

Encrypted Matching Pipeline

• Implement vector encryption (CKKS/FHE) for face embeddings.
• Develop threshold-based similarity checks in encrypted space (GPU-accelerated).
• Collaborate on algorithm selection (cosine similarity vs. alternatives) ensuring high precision at 95%+ thresholds.

Multi-Sensor Data Fusion

• Synchronize and process input from multiple camera modules.
• Fuse thermal/IR/depth data to improve accuracy and spoof resistance.

Real-Time Performance Engineering

• Achieve sub-second processing latency.
• Optimize compute graph, memory usage, and sensor I/O.

Hardware Integration

• Work closely with embedded engineers to integrate ML pipelines into the device’s OS and BSP.

R&D

• Stay updated on state-of-the-art in biometric security, encrypted ML, and edge AI.
• Prototype and test new methods for privacy-preserving identity verification.

Required Skills

Core ML / CV Skills

• Strong background in computer vision (OpenCV, PyTorch/TensorFlow).
• Experience with face recognition systems (e.g., ArcFace, FaceNet) and anti-spoofing.
• Model optimization for constrained devices (TensorRT, pruning, quantization).

Embedded AI

• NVIDIA Jetson platform experience (Nano, Xavier, Orin).
• CUDA, cuDNN, GPU profiling, and performance tuning.

Privacy-Preserving ML

• Hands-on with Fully Homomorphic Encryption (CKKS) / SMPC or related frameworks (e.g., OpenFHE, SEAL, FIDESlib).
• Understanding of secure enclaves and encrypted inference.

Systems & Integration

• Comfortable working with BSP bring-up, camera sensor integration, and custom drivers.
• Strong Python & C++ skills for production deployment.

Bonus

• Depth/thermal imaging experience.
• Knowledge of biometric standards & certification (ISO/IEC 19794-5).
• Background in security for identity systems.

Ideal Candidate

• Has deployed ML models on embedded GPU hardware.
• Has worked on biometric authentication or high-security identity verification projects.
• Can own the full stack of data processing — from raw sensor input to encrypted decision output.
• Thrives in R&D-heavy, rapid-prototyping environments.

Branch Overview

Branch delivers world-class financial services to the mobile generation. With offices in the United States, Nigeria, Kenya, and India, Branch is a for-profit socially conscious company that uses the power of data science to reduce the cost of delivering financial services in emerging markets. We believe that everyone everywhere deserves fair financial access. The rapid spread of smartphones presents an opportunity for the world’s emerging middle class to access banking options and achieve financial flexibility.

Branch’s mission-driven team is led by the founder and former CEO of Kiva.org. The company presents a rich opportunity for our team members to drive meaningful growth in rapidly evolving and changing markets. In 2019, Branch announced our Series C and garnered more than $100M in funding with investments from leading Silicon Valley firms, including Andreessen Horowitz, Trinity Capital, Foundation Capital, Visa, and the International Finance Corporation (IFC).

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As a product-driven org, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we create an environment where everyone feels empowered to propose solutions to the challenges we face.

We value diversity and are committed to providing an inclusive working environment where human beings of all backgrounds can thrive.

Job Overview

Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.

Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.

Responsibilities

• Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.
• Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.
• Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.
• Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.

Qualifications

• 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.
• Excellent software engineering and programming skills, especially Python and SQL.
• A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.
• A deep understanding of using cloud computing infrastructure and data pipelines in production.
• Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.
• Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.
• The drive to make a positive impact on customers' lives.

Benefits of Joining

• Mission-driven, fast-paced, and entrepreneurial environment
• Competitive salary and equity package
• A collaborative and flat company culture
• Fully-paid Group Medical Insurance and Personal Accidental Insurance
• Unlimited paid time off, including personal leave, bereavement leave, and sick leave
• Fully paid parental leave — 6 months maternity leave and 3 months paternity leave
• Monthly WFH stipend alongside a one-time home office set-up budget
• $500 Annual professional development budget
• Team meals and social events — Virtual and In-person

We’re looking for more than just qualifications -- if you’re unsure that you meet the criteria but identify with our vision of providing equal opportunity to everyone to access financial services, please do not hesitate to apply!

Branch International is an Equal Opportunity Employer. The company does not and will not discriminate in employment on any basis prohibited by applicable law.

Machine Learning Engineer

About Astreya:

Astreya offers comprehensive IT support and managed services. These services include Data

Center and Network Management, Digital Workplace Services (like Service Desk, Audio Visual, and

IT Asset Management), as well as Next-Gen Digital Engineering services encompassing Software

Engineering, Data Engineering, and cybersecurity solutions. Astreya's expertise lies in creating

seamless interactions between people and technology to help organizations achieve operational

excellence and growth.

Responsibilities:

• Design, develop, and deploy machine learning models and algorithms to solve complex business problems and drive data-driven decision making
• Collaborate with cross-functional teams including data engineers, software engineers, and business stakeholders to understand requirements and translate business objectives into scalable ML solutions
• Build and maintain robust ML pipelines for data preprocessing, feature engineering, model training, validation, and deployment
• Optimize model performance through hyperparameter tuning, feature selection, and algorithmic improvements
• Implement MLOps best practices including model versioning, monitoring, and automated retraining workflows
• Ensure data quality, integrity, and security throughout the ML lifecycle
• Scale ML systems to handle large datasets and high-throughput inference requirements
• Conduct A/B testing and experimentation to validate model performance and business impact
• Monitor deployed models for drift, performance degradation, and bias detection
• Create comprehensive documentation including technical specifications, model cards, and deployment guides for stakeholders

Professional & Technical Skills:

• Must have strong proficiency in Python and experience with core ML libraries such as scikit-learn, XGBoost, LightGBM, and CatBoost
• Must have hands-on experience with deep learning frameworks including TensorFlow, PyTorch
• Must have solid understanding of machine learning algorithms, statistical methods, and model evaluation techniques
• Must have experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies Docker or Kubernetes
• Need to have proficiency in SQL and experience working with both structured and unstructured datasets
• Need to have knowledge of big data technologies such as Spark, Hadoop, or distributed computing frameworks
• Must be familiar with MLOps tools and platforms such as MLflow, Kubeflow, or similar model lifecycle management systems
• Must have experience with version control systems (Git) and CI/CD pipelines for ML workflows
• Need to have knowledge of data visualization tools and libraries such as Matplotlib, Seaborn, Plotly, or Tableau
• Must be familiar with software engineering best practices, including code testing, debugging, and performance optimization
• Need to have understanding of software development methodologies such as Agile or Scrum
• Possess excellent analytical and problem-solving skills with ability to work independently and in team environments

Additional Information:

• Must have Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related quantitative field
• Preferred 3+ years of experience in machine learning engineering or related roles
• Preferred experience with real-time inference systems and model serving architectures

Preferred knowledge of specialized domains such as computer vision, natural language processing, or recommendation systems

What You’ll Do

• Collaborate 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 Are

• 2–5 years experience in machine learning engineering or applied data science.
• Strong programming skills in Python (PyTorch, TensorFlow, 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).

Are you a talented Data Scientist (includes AI/ML Researcher, AI/ML Engineer, Data Engineer, ML Ops Engineer, QA Engineer with AI/ML focus, NLP Engineer, LLM Engineer) either,

• Looking for your next big challenge working remotely OR

• Employed , but open to offers from elite US companies to work remotely?

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• Experience . Must have at least 3 years of experience .

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• Skills . TensorFlow, PyTorch, Scikit-learn Python, Java, C++, R, AWS, Azure, GCP, (SQL, NoSQL, Hadoop, Spark, Docker, Kubernetes, AWS Redshift, Google BigQuery.

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