Machine Learning Job Vacancies in Vijayawada

ROLE OVERVIEWYou will be responsible for building, maintaining and productionizing the backend infrastructure of VAMS ATLAS.The platform must support:* Deterministic scientific computation* Reproducible pipeline execution* Immutable/versioned reference artifacts* PostgreSQL-backed registries* Asynchronous computational workloads* API services* Audit trails and provenance* Evidence and entitlement gating* Report generation contracts* Cloud object storage* Production observability* Secure integration with frontend applicationsCORE RESPONSIBILITIES1. Backend API DevelopmentDevelop and maintain backend services and APIs supporting the VAMS BIOME ecosystem.2. PostgreSQL & Data ArchitectureOwn and extend the ATLAS PostgreSQL data layer. The engineer will work with registries covering areas such as:* samples* sequencing runs* analysis runs* score definitions* panels* conditions* reference cohorts* reference artifact sets* pipeline/version metadata* QC flags* confidence penalties* report outputs* audit recordsScientific outputs must remain traceable to the exact configuration and artifacts from which they were generated.3. Reference Artifact RegistryImplement and maintain the VAMS ATLAS Reference Artifact Registry.4. Deterministic Reference SelectionImplement deterministic selection of reference cohorts/artifacts based on analysis context.5. Analysis Run OrchestrationBuild and maintain the execution layer connecting backend services with computational/bioinformatics pipelines.The engineer is not expected to invent microbiome algorithms.Bioinformatics and scientific teams define biological processing and interpretation logic.The backend engineer makes these pipelines reliable, deterministic, scalable and auditable.6. Two-Mode Execution ArchitectureThe platform maintains strict separation on Cohort Build ModeUsed offline to construct and register approved reference artifacts.7. Auditability & ProvenanceEvery ATLAS run must generate sufficient provenance to reconstruct the analysis.Where appropriate, computational outputs should have integrity hashes.A historical report should be traceable back to its computational inputs and configuration.8. Scientific Governance EnforcementThe backend is responsible for enforcing scientific governance supplied by the scientific/Founders Office configuration.9. Reporting BackendDevelop structured report objects by:* VAMS ATLAS web applications* downloadable reports* clinician-facing interfaces* future mobile applications* analytics and internal systems10. Cloud & InfrastructureHelp operate and evolve the cloud execution architecture.Expected areas include:* AWS* S3/object storage* containerized workloads* Docker* Asynchronous jobs/queues* Worker infrastructure* CI/CD* Environment management* Secrets management* Log/ Monitor* Health checksExperience with one or more of the following is valuable:* AWS Batch* ECS/Fargate* Step Functions* Lambda* SQS* EventBridge* CloudWatchEquivalent production cloud experience is acceptable.11. Security & Production EngineeringImplement secure engineering practices across the backend.Experience working with health, genomic or other sensitive datasets is advantageous.REQUIRED TECHNICAL SKILLSCandidates should have strong practical experience with most of the following:Backend* Python* FastAPI or comparable modern Python API framework* Pydantic / schema validation* REST API design* asynchronous/background processingDatabase* PostgreSQL* SQL* relational schema design* migrations* constraints and indexes* transactional systems* JSON/JSONBInfrastructure* Docker* Linux* Git / GitHub* CI/CD* AWS or equivalent cloud infrastructure* object storage such as S3* environment and secrets managementEngineering* Automated testing* API testing* Integration testing* Structured logging* Exception handling* Idempotent operations* Versioning* Reproducible executionSTRONGLY PREFERRED EXPERIENCECandidates with experience in any of the following will be particularly valuable:* Bioinformatics* Genomics* Microbiome data* Scientific computing* Health-tech* Clinical software* Laboratory data systems* Workflow orchestration* Data engineering* ML/data pipelines* Reproducible computational pipelinesFamiliarity with concepts such as FASTQ, sequencing pipelines, reference databases or computational provenance is advantageous but not mandatory.Important Role BoundaryThis position owns engineering implementation, not independent scientific decision-making.The Backend / Platform Engineer should not independently:* Invent microbiome scoring formulas* Modify biological thresholds* Change evidence tiers* Determine whether datasets are scientifically valid* Redefine condition mappings* Reinterpret microbiome biology* Modify scientific recommendationsThose decisions are supplied through governed scientific specifications.The engineers responsibility is to ensure those specifications are implemented correctly, deterministically, securely and audibly.What Success Looks LikeWithin the first few months, the successful engineer should be able to demonstrate that:1. ATLAS backend services can reliably execute production analysis workflows.2. Every analysis run is versioned and auditable.3. Historical analyses can identify the exact reference artifacts used.4. Reference artifacts cannot be accidentally modified by production user workflows.5. Scientific gating is enforced server-side.6. Backend APIs expose stable contracts to frontend applications.7. Failed computational jobs can be diagnosed and recovered safely.8. Automated tests cover critical backend and governance rules.9. Production services have appropriate logging, monitoring and health checks.10. The platform can scale from Phase-1 operations toward substantially larger sample volumes without architectural replacement.Candidate ProfileWe are particularly interested in engineers who enjoy building systems where correctness matters more than simply shipping endpoints.You may be a good fit if you:* Think carefully about system boundaries* Understand database integrity* Prefer deterministic systems over hidden behavior* Write testable code* Document architectural decisions* Are comfortable reading technical/scientific specifications* Can work independently* Can challenge ambiguous requirements constructively* Understand that scientific software requires stronger provenance than ordinary consumer applicationsMinimum Qualifications* Bachelors degree in Computer Science, Software Engineering, Information Technology or related discipline, or equivalent demonstrated engineering experience* Approximately 3+ years of professional backend/software engineering experience* Strong Python skills* Strong PostgreSQL/SQL skills* Experience building production APIs* Experience with Docker and Git* Experience deploying or operating cloud-based systems* Good understanding of software testing and production debuggingPreferred Qualifications* 4-6+ years backend/platform experience* FastAPI production experience* AWS architecture experience* Workflow/orchestration experience* Bioinformatics or computational biology exposure* Experience handling sensitive health/scientific data* Experience building reproducible data-processing systems* Infrastructure-as-code experience* Strong automated testing practices* Experience with observability and production incident debuggingWHAT TO SUBMITInterested candidates should submit the ff:* Resume/CV* GitHub profile or examples of previous technical work where available* Brief description of a backend/platform system they personally designed or substantially implemented* Technologies used* Their specific contribution to the architectureShortlisted candidates will complete a technical discussion and practical architecture/coding assessment focused on backend engineering, PostgreSQL, APIs, deterministic processing and production system design.

Job Title: Artificial Intelligence (AI) TrainerLocation: Vijayawada, Andhra PradeshExperience: 25 YearsJob Summary:We are looking for a skilled and enthusiastic AI Trainer to deliver comprehensive training programs in Artificial Intelligence and Machine Learning. The ideal candidate should have hands-on experience in Python programming, data handling, and developing AI/ML models, along with a passion for teaching and mentoring learners at various levels.Key Responsibilities:Deliver structured and engaging training sessions on AI, ML, and Data Science conceptsTeach foundational to advanced topics using Python, libraries, and ML frameworksGuide learners through hands-on projects, assignments, and case studiesDevelop course materials, coding exercises, and assessmentsConduct evaluations, mock interviews, and doubt-clearing sessionsStay updated with the latest tools, techniques, and trends in AI/MLAssist students in building real-time capstone projectsRequired Qualifications:Bachelors or Masters degree in Computer Science, Engineering, Data Science, or related fieldStrong foundation in Python, statistics, and machine learning algorithms25 years of experience in training, development, or applied machine learning rolesExcellent communication skills and ability to explain complex concepts in simple terms

Hiring for 25 AI agent Developer Jobs in Visakhapatnam, Bhubaneswar, Hyderabad, Vijayawada, India, for Freshers,Required Educational Qualification is : Professional Degree, B.Com, B.Sc, B.Tech, M.B.A/PGDM, M.Sc with Good knowledge in An AI Agent Developer requires expertise in programming languages such as Python, Java, JavaScript, C , TypeScript, and Go. Strong knowledge of machine learning (ML), deep learning (DL), reinforcement learning (RL), and generative AI is essential. They must be proficient in large language models (LLMs), prompt engineering, model fine-tuning, supervised and unsupervised learning, transfer learning, and neural networks. Expertise in natural language processing (NLP) is crucial, including named entity recognition (NER), speech recognition, sentiment analysis, text summarization, tokenization, text-to-speech (TTS), speech-to-text (STT), and semantic search. A deep understanding of data science and engineering is needed, covering data preprocessing, feature engineering, data cleaning, statistical analysis, and time-series forecasting. Knowledge of retrieval-augmented generation (RAG), vector databases like FAISS, Pinecone, and Weaviate, knowledge graphs, hybrid search, and frameworks like LangChain and Llama Index is valuable. Proficiency in DevOps and MLOps, including Docker, Kubernetes, CI/CD pipelines, API development, cloud computing (AWS, GCP, Azure), model deployment, and serverless computing, is essential for scaling AI applications. Familiarity with AI tools and frameworks such as PyTorch, TensorFlow, Scikit-learn, OpenAI API, Hugging Face Transformers, FastAPI, Flask, Django, and GraphQL is beneficial. A strong focus on security and compliance, including data security, privacy, GDPR, AI ethics, and bias detection, is necessary. Additionally, soft skills like problem-solving, critical thinking, communication, collaboration, and continuous learning help AI Agent Developers adapt to new challenges and innovations., AI, AI Developer etc.