

Orenda Financial Services
https://orendafinserv.comAbout
Orenda
Candid answers by the company
Ahmedabad
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Jobs at Orenda Financial Services

About the Role
We are looking for a creative and hands-on Graphic Designer & Video Editor who can create high-quality visual content for our advertising and social media channels.
You will be responsible for creating static ad creatives, social media graphics, reels, customer testimonials, and simple explainer videos. This role is ideal for someone who enjoys working on multiple creative ideas, producing content quickly, and adapting designs based on campaign requirements.
Since we operate in the financial services industry, we value clarity, professionalism, trust, and credibility over overly flashy designs. Your work should make our brand look reliable, professional, and easy to understand.
What You'll Own
1. Graphic Design
- Create engaging ad creatives and social media posts for Instagram, Facebook, LinkedIn, and other digital platforms.
- Develop creatives for marketing campaigns, promotions, and brand communication.
- Create multiple design variations based on campaign requirements.
2. Video Editing
- Edit short-form videos such as Instagram Reels, customer testimonials, promotional videos, and simple explainer videos.
- Add appropriate transitions, text, subtitles, music, and other elements to make videos engaging and easy to understand.
- Adapt video content into different formats and sizes for various platforms.
3. Creative Volume & Testing
- Produce multiple creative concepts and variations within short timelines.
- Work closely with the marketing team to develop creatives that can be A/B tested.
- Understand campaign objectives and convert marketing ideas into effective visual content.
4. Brand Consistency
- Ensure all creatives follow the company's brand guidelines, visual identity, and communication standards.
- Maintain a professional and trustworthy visual language suitable for the financial services industry.
- Ensure that content is clear, accurate, and appropriate for the intended audience.
5. Collaboration
- Work closely with the Performance Marketing and Marketing teams to understand campaign objectives.
- Convert campaign briefs and ideas into ready-to-use creatives.
- Manage multiple creative requirements and deliver them within agreed timelines.
What We're Looking For
- 1–3 years of experience in Graphic Design, Video Editing, or a similar creative role.
- Strong knowledge of Adobe Photoshop, Illustrator, Premiere Pro, After Effects, Canva, or similar tools.
- Good understanding of social media design and short-form video content.
- Ability to create clean, professional, and visually appealing designs.
- Ability to work on multiple creative requirements with tight deadlines.
- Strong attention to detail and understanding of typography, layouts, colors, and visual hierarchy.
- A good understanding of current social media trends and creative formats.
- Ability to take feedback positively and make quick revisions.
Good to Have
- Experience working with financial services, fintech, banking, lending, or other regulated industries.
- Experience creating performance marketing creatives.
- Basic understanding of A/B testing and digital advertising.
- Experience with motion graphics and simple animations.
What You'll Get
- Opportunity to work closely with the Marketing and Performance Marketing teams.
- Exposure to real-world digital marketing campaigns and creative testing.
- Opportunity to work on a wide variety of design and video content.
- A fast-paced environment where your creative work directly contributes to business growth.
If you are someone who can turn ideas into clean, effective, and high-performing visual content, we'd love to hear from you.
About the role
We are building AI systems that read, understand and act on real business documents, bank statements, financial reports, policy documents and forms and putting them into production where accuracy and cost both matters.
This is not a research role and it is not a prompt-writing role. You will own features end to end: pick and deploy open-source models, build the pipelines around them, measure whether they actually work on our documents, drive the cost per document down, and keep the whole thing running in production.
You will work closely with the engineering and product teams, and your work will be directly used by business users from day one.
What you will do
Deploy and evaluate open-source models
- Select, deploy and benchmark open-source LLMs and vision-language models for specific, narrow use cases not general chat.
- Build evaluation sets from real documents and define what "good" means numerically (field-level accuracy, extraction recall, hallucination rate) before shipping.
- Run structured comparisons between models and approaches, and write up the trade-offs so the team can make a decision.
- Apply quantization, batching and other optimizations to fit models into a sensible GPU budget.
Build and optimize AI orchestration
- Design multi-step pipelines that combine deterministic code, ML models and LLM calls and know when not to use an LLM.
- Optimize for latency, cost and reliability: caching, batching, request routing, fallback tiers, retries and graceful degradation.
- Instrument pipelines so failures are visible and traceable rather than silent.
Ship to production
- Package models and services with Docker, expose them behind clean APIs, and deploy them to our GPU and CPU infrastructure.
- Handle the unglamorous production concerns: cold starts, timeouts, concurrency limits, versioning, rollback and monitoring.
- Own on-call-style responsibility for the AI features you build, including cost tracking.
Must-have skills
Programming & engineering
- Strong Python: type hints, async/await, dataclasses/Pydantic, clean module design, testing.
- REST API development with FastAPI (or Flask/Django with a willingness to move to FastAPI).
- Git, code review discipline, and the ability to write code someone else can maintain.
- Comfortable in Linux and on the command line.
Machine learning fundamentals
- Working knowledge of PyTorch and the Hugging Face ecosystem (transformers, tokenizers, accelerate).
- Understanding of inference-time concepts: tokenization, context windows, batching, precision (FP16/BF16/INT8), memory footprint.
- Ability to read a model card and a paper well enough to judge whether a model fits a use case.
Document processing
- Hands-on experience with at least two of: pypdfium2, PyMuPDF, pdfplumber, pdfminer.six, Docling, Unstructured, Surya, DocTR, LayoutLM family.
- Practical OCR experience (Tesseract, PaddleOCR, or a cloud OCR) and an understanding of when OCR is the wrong tool.
- Experience extracting tables from PDFs and dealing with merged cells, multi-line rows, and inconsistent column layouts.
Strongly preferred
You will be a much stronger candidate with any of these. We do not expect all of them.
Model serving & optimization
- vLLM, TGI, Ollama, llama.cpp, or Triton Inference Server.
- Quantization formats and tooling: GGUF, AWQ, GPTQ, bitsandbytes, ONNX Runtime, INT8 export.
- Serverless GPU platforms: Modal, RunPod, Replicate, Baseten including cold-start and container-lifecycle management.
- LoRA / QLoRA fine-tuning with PEFT for narrow, task-specific improvements.
Vision-language models
- Practical use of open VLMs: Qwen2.5-VL, InternVL, Granite Vision, Molmo, Phi-Vision, or similar.
- Awareness of where VLMs hallucinate especially on numeric and financial content and patterns for constraining them (using the model for layout only, sourcing values from the text layer, constrained decoding).
Orchestration & pipelines
- Workflow orchestration: Dagster, Airflow, Prefect, or Temporal.
- Async job patterns: Celery, RQ, or platform-native spawn/poll patterns.
- LLM orchestration frameworks (LangGraph, LlamaIndex, Haystack) with the judgement to know when plain Python is a better answer.
- Structured output enforcement: Instructor, Outlines, XGrammar, JSON schema / tool-use modes.
Evaluation & observability
- Building golden datasets and regression suites for extraction tasks.
- Eval tooling: promptfoo, DeepEval, Ragas, or in-house harnesses.
- LLM tracing and monitoring: Langfuse, Arize Phoenix, LangSmith, OpenTelemetry.
Nice extras
- Rule engines and policy evaluation (Open Policy Agent / Rego, Drools, rule-engine).
- Experience in fintech, lending, insurance or accounting documents.
- Handling of PII and data-security practices in document pipelines.
- Contributions to open-source ML or document-processing projects.
Why join us
- Real production ownership from month one your work goes to actual users, not a demo.
- Genuinely hard technical problems in document AI, not wrappers over an API.
- Small team, short decision cycles, direct access to leadership.
- Budget and freedom to evaluate and adopt new open-source models as they land.
To apply: send your CV along with a short note on one AI system you have taken to production what it did, what the accuracy was, and what broke.
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