Qureos Mentor

Xerago

We are seeking a highly experienced Senior Python Developer (5+ years) with strong expertise in backend development, data engineering, and hands-on AI/ML project execution. In this role, you will design and build scalable applications, data pipelines, and automation systems while collaborating with cross-functional teams including data scientists, analysts, and product managers.The ideal candidate has deep Python knowledge, strong database fundamentals, and proven experience delivering AI-driven solutions from prototype to production.Key ResponsibilitiesBackend &amp; Application Development<ul><li>Design, develop, and maintain scalable Python applications and backend services.</li><li>Write clean, efficient, and modular code following best software engineering practices.</li><li>Build automation tools, internal utilities, and workflow systems to optimize business processes.</li><li>Develop RESTful APIs and integrations with third-party services and internal systems.</li></ul>AI/ML Engineering<ul><li>Work directly with data scientists to implement, optimize, and deploy machine learning models.</li><li>Build end-to-end ML pipelines including data preprocessing, feature engineering, inference services, monitoring, and model retraining workflows.</li><li>Apply ML techniques such as regression, classification, clustering, and time-series analysis to solve real business problems.</li></ul>Data Engineering &amp; Pipelines<ul><li>Develop robust ETL/data ingestion pipelines to collect, clean, and transform data from diverse sources.</li><li>Design efficient SQL and NoSQL database schemas for structured and unstructured data.</li><li>Optimize query performance, indexing strategies, and storage solutions for high-volume datasets.</li></ul>System Reliability &amp; Optimization<ul><li>Monitor and debug production systems to ensure performance, reliability, and scalability.</li><li>Optimize Python code for speed, memory usage, and efficiency.</li><li>Implement automated testing, CI/CD pipelines, and version control best practices.</li></ul>Collaboration &amp; Leadership<ul><li>Collaborate with product, analytics, and engineering teams to gather requirements and deliver technical solutions.</li><li>Conduct code reviews, enforce coding standards, and mentor junior developers.</li><li>Contribute to architectural decisions and long-term technology strategy.</li></ul>Required Skills &amp; Qualifications<ul><li>5+ years of professional experience in Python development.</li><li>Expertise in Python libraries such as Pandas, NumPy, FastAPI/Flask, AsyncIO, and multiprocessing.</li><li>Hands-on experience with AI/ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.</li><li>Strong understanding of ML concepts (regression, classification, time-series forecasting, clustering).</li><li>Solid SQL skills including complex joins, aggregations, indexing, and schema design.</li><li>Experience with NoSQL databases (e.g., MongoDB, Redis, Cassandra) is a plus.</li><li>Strong experience with API integration and building/consuming RESTful services.</li><li>Ability to design and maintain scalable ETL and data ingestion pipelines.</li><li>Strong debugging, problem-solving, and performance optimization skills.</li><li>Familiarity with Git, CI/CD pipelines, and modern development workflows.</li><li>Excellent communication and collaborative skills.</li></ul>Job Type: Full-timeExperience:<ul><li>Python: 5 years (Required)</li><li>AI: 4 years (Required)</li></ul>Work Location: In person

Senior Python Developer

Roles &amp; Responsibilities:<ul><li>Architect scalable AI solutions: Define end-to-end reference architectures (LLM/RAG, NLP, vision, agentic workflows) that move cleanly from DemoBytes &rarr; POC &rarr; MVP &rarr; Demoable &rarr; Production.</li><li>Own full-stack delivery: Build features across data/ML, backend APIs/services (FastAPI/Flask), and lightweight UIs (React/Next.js) for demoable, user-ready outputs.</li><li>Rapid prototyping: Stand up POCs in days; harden validated solutions into MVP and production with incremental quality/security gates.</li><li>MLOps &amp; platformization: Implement CI/CD/CT for models, datasets, prompts; automate evals, canary/rollback, versioning, model/data drift monitoring, and experiment tracking (W&amp;B/MLflow).</li><li>Integration &amp; interoperability: Embed AI into existing products and workflows via APIs, queues, SDKs, and webhooks with clear SLAs and observability.</li><li>Operate what you build: Instrument services, track p95 latency/availability/cost, and drive continuous improvement post-launch.</li><li>Mentor &amp; uplift: Coach engineers on best practices (prompting, vector design, evals, latency/cost tuning, secure data handling).</li><li>Release cadence: Maintain monthly demo releases and production releases every two months with ALM-driven governance.</li><li>Ethical AI &amp; compliance: Apply privacy-by-design, bias testing/mitigation, model cards, auditability, and data protection controls; ensure documentation in ALM.</li><li>Trendwatching: Track state-of-the-art AI (models, toolchains, infra) and pragmatically incorporate breakthroughs into roadmaps.</li></ul>Qualifications:<ul><li>4&ndash;6 years delivering AI/ML features to production with fast POC &rarr; MVP &rarr; Production cycles.</li><li>Strong ML/DL fundamentals; hands-on with PyTorch and/or TensorFlow/Keras; LLMs (prompting, fine-tuning/LoRA), RAG patterns, and evaluation.</li><li>Python proficiency; scikit-learn, spaCy/NLTK; Hugging Face (Transformers/Datasets/PEFT); familiarity with YOLO/FastAI (role-relevant).</li><li>Backend engineering for production (FastAPI/Flask), auth, caching, testing; practical React/Next.js for demoable UIs.</li><li>MLOps: Docker/Kubernetes, CI/CD (GitHub Actions/Azure DevOps/Jenkins), experiment tracking (Weights &amp; Biases/MLflow), monitoring (Prometheus/Grafana/OpenTelemetry).</li><li>Data &amp; storage: SQL/NoSQL (Postgres, Redis), object stores; vector DBs (FAISS/Milvus/pgvector) and retrieval design.</li><li>Cloud: AWS/Azure/GCP with cost/latency/performance trade-off literacy.</li><li>AI productivity tools (required): Cursor, Windsurf, Claude, Copilot for accelerated prototyping, code gen/review, and prompt workflows.</li><li>Effective communication; crisp documentation and governance in ALM.</li><li>Working knowledge of ethical AI and data protection (PII handling, access controls, audit trails).</li></ul>Job Type: Full-timeExperience:<ul><li>AI: 4 years (Required)</li><li>Python: 4 years (Required)</li></ul>Work Location: In person

Senior AI Engineer

Job Description:&middot; Developing models: Building and improving mathematical models for trading, forecasting, or data processing&middot; Conducting research: Analyzing large datasets to identify trends and insights, and conducting research on financial markets and economic conditions&middot; Back testing: Testing and implementing trading models and signals in a live trading environment&middot; Creating reports: Summarizing findings and insights in detailed documents or presentations for non-technical stakeholders&middot; Using unconventional data: Using unconventional data sources to drive innovation&middot; Translating algorithms: Translating algorithms into code&middot; Managing portfolios: Managing and fine-tuning investment portfolios to maximize returns while minimizing risks&middot; Product Notes: Writing a detailed Product Note with all information including data to support the strategy&middot; Pseudo Code: Capability to write Pseudo Code to test the strategy&middot; Systems: Good understanding of the Trading Systems and trade execution process to limit latency and slippagesInvestment Management:&middot; Oversee the development and implementation of investment strategies and asset allocation models.&middot; Monitor market trends and economic indicators to make informed investment decisions.&middot; Ensure adherence to the firm&rsquo;s investment policies and risk management guidelines.Compliance and Risk Management:&middot; Ensure the firm&rsquo;s practices comply with SEBI regulations and other relevant legal requirements.&middot; Conduct periodic audits and reviews to maintain high standards of regulatory compliance.&middot; Implement and monitor internal controls to manage and mitigate risks effectively.Qualifications:&middot; Bachelor&rsquo;s degree in finance, economics, business administration, or a related field; advanced degrees (MBA, CFA, CFP) preferred.&middot; Relevant experience in mathematics, statistics, computer science, or finance preferred&middot; NISM Series XV and Series X A&amp;B certification&middot; Minimum of 5-10 years of experience in building technical trading and Quantitative Strategies&middot; Deep knowledge of SEBI regulations and compliance requirements.&middot; Proven ability to develop and execute strategic initiatives.&middot; High ethical standards and a commitment to acting in clients' best interests.Job Type: Full-timeExperience:<ul><li>Quantitative research: 4 years (Required)</li></ul>Work Location: In person

Quantitative Research Analyst

We are looking for a dedicated PPC Specialist with 4+ years of hands-on experience in managing and optimizing paid advertising campaigns. The ideal candidate will be responsible solely for Paid Ads, with strong expertise in Google Ads, Meta Ads, and LinkedIn Ads. Experience handling paid campaigns for financial institutions or BFSI clients is a strong plus.Key Responsibilities:<ul><li>Plan, create, and optimize campaigns across Google Ads (Search, Display, Video, Performance Max), Meta Ads (Facebook &amp; Instagram), and LinkedIn Ads.</li><li>Conduct keyword research, audience segmentation, and competitor analysis to improve campaign performance.</li><li>Monitor daily campaign performance and implement data-driven optimizations.</li><li>Develop and execute strategies to achieve lead generation, acquisition, and brand objectives.</li><li>Manage budgets, forecasts, pacing, and monthly spending.</li><li>Create ad copies, CTA variations, and coordinate with the creative team for ad assets.</li><li>Track and measure campaign performance using platforms like Google Analytics, Google Tag Manager, and other tracking tools.</li><li>Prepare weekly and monthly performance reports with insights and optimization recommendations.</li><li>Stay updated with platform trends, new features, and advertising best practices.</li><li>Support the SEO team with keyword insights, data sharing, or basic SEO tasks when required.</li></ul>Required Skills &amp; Experience:<ul><li>4+ years of experience managing end-to-end paid ad campaigns.</li><li>Strong expertise in Google Ads, Meta Ads, and LinkedIn Ads.</li><li>Good understanding of conversion tracking, attribution, audience targeting, and remarketing strategies.</li><li>Hands-on experience with Google Analytics, GTM, UTM tracking, and pixel setups.</li><li>Proven ability to deliver strong ROI and meet lead/acquisition targets.</li><li>Excellent analytical, problem-solving, and optimization skills.</li><li>Ability to work independently with ownership and accountability.</li><li>Experience working with financial institutions/BFSI clients is a strong advantage.</li><li>Exposure to other ad platforms like TikTok Ads, X Ads (Twitter), and programmatic DSPs.</li><li>Familiarity with landing page optimization, CRO, and funnel performance.</li><li>Working knowledge of SEO fundamentals (on-page optimization, keyword research, and basic technical SEO).</li></ul>Job Type: Full-timeWork Location: In person

Performance Marketing Specialist

Join Xerago and explore 4   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Xerago

ABOUT_COMPANY

Senior Python Developer

Senior AI Engineer

Quantitative Research Analyst

Performance Marketing Specialist