Outsystems Developer

🎯 Ideal Candidate Profile:

This role requires a seasoned engineer/scientist with a strong academic background from a premier institution and significant hands-on experience in deep learning (specifically image processing) within a hardware or product manufacturing environment.

📋 Must-Have Requirements:

Experience & Education Combinations:

Candidates must meet one of the following criteria:

• Doctorate (PhD) + 2 years of related work experience
• Master's Degree + 5 years of related work experience
• Bachelor's Degree + 7 years of related work experience

Technical Skills:

• Minimum 5 years of hands-on experience in all of the following:
• Python
• Deep Learning (DL)
• Machine Learning (ML)
• Algorithm Development
• Image Processing
• 3.5 to 4 years of strong proficiency with PyTorch OR TensorFlow / Keras.

Industry & Institute:

• Education: Must be from a premier institute (IIT, IISC, IIIT, NIT, BITS) or a recognized regional tier 1 college.
• Industry: Current or past experience in a Product, Semiconductor, or Hardware Manufacturing company is mandatory.
• Preference: Candidates from engineering product companies are strongly preferred.

ℹ️ Additional Role Details:

• Interview Process: 3 technical rounds followed by 1 HR round.
• Work Model: Hybrid (requiring 3 days per week in the office).

Based on the job description you provided, here is a detailed breakdown of the Required Skills and Qualifications for this AI/ML/LLM role, formatted for clarity.

📝 Required Skills and Competencies:

💻 Programming & ML Prototyping:

• Strong Proficiency: Python, Data Structures, and Algorithms.
• Hands-on Experience: NumPy, Pandas, Scikit-learn (for ML prototyping).

🤖 Machine Learning Frameworks:

• Core Concepts: Solid understanding of:
• Supervised/Unsupervised Learning
• Regularization
• Feature Engineering
• Model Selection
• Cross-Validation
• Ensemble Methods: Experience with models like XGBoost and LightGBM.

🧠 Deep Learning Techniques:

• Frameworks: Proficiency with PyTorch OR TensorFlow / Keras.
• Architectures: Knowledge of:
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Long Short-Term Memory networks (LSTMs)
• Transformers
• Attention Mechanisms
• Optimization: Familiarity with optimization techniques (e.g., Adam, SGD), Dropout, and Batch Normalization.

💬 LLMs & RAG (Retrieval-Augmented Generation):

• Hugging Face: Experience with the Transformers library (tokenizers, embeddings, model fine-tuning).
• Vector Databases: Familiarity with Milvus, FAISS, Pinecone, or ElasticSearch.
• Advanced Techniques: Proficiency in:
• Prompt Engineering
• Function/Tool Calling
• JSON Schema Outputs

🛠️ Data & Tools:

• Data Management: SQL fundamentals; exposure to data wrangling and pipelines.
• Tools: Experience with Git/GitHub, Jupyter, and basic Docker.

🎓 Minimum Qualifications (Experience & Education Combinations):

Candidates must have experience building AI systems/solutions with Machine Learning, Deep Learning, and LLMs, meeting one of the following criteria:

• Doctorate (Academic) Degree + 2 years of related work experience.
• Master's Level Degree + 5 years of related work experience.
• Bachelor's Level Degree + 7 years of related work experience.

⭐ Preferred Traits and Mindset:

• Academic Foundation: Solid academic background with strong applied ML/DL exposure.
• Curiosity: Eagerness to learn cutting-edge AI and willingness to experiment.
• Communication: Clear communicator who can explain ML/LLM trade-offs simply.
• Ownership: Strong problem-solving and ownership mindset.

We are seeking a proactive and experienced HR Manager to lead and manage our HR team. The ideal candidate will be responsible for refining job profiles, handling end-to-end recruitment, and ensuring a positive and engaging work culture for all employees.

We are looking out for an iOS Developer to join the Mobile team to take end to end ownership of our iOS Consumer App. We are looking out for someone who speaks fluent Swift and loves shipping and building beautiful, maintainable and scalable apps.

Requirements:

• You have 2-6 years of experience working with Swift and Objective-C whenever you encounter the pitfalls of Swift.
• Familiarity with MVC, MVP, MVVM and VIPER architectures.
• You have worked on 2-3 production apps with MAU's in the range of 25K+.
• You love getting your hands dirty and are dealing with legacy parts of the code bases.
• You have experience building projects from scratch as well as building on top of existing code bases.
• You have handled complex views ranging from Form Heavy views to Animation Heavy views.
• You have a strong bias towards action.

Good to have:

• Experience dealing with Location Data along with Mapping interfaces like Google Maps, Map Box or MapMyIndia.
• Experience implementing CI/CD, Automated Tests and Unit Testing.
• Experience with RxSwift, Alamofire, Kingfisher, Lottie, SwiftyBeaver, Firebase SDK, Clevertap SDK and ObjectMapper.
• Implementing designs w. r. t HCI guidelines.

Lead Data Engineer

Data Engineers develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems. On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product. It could also be a software delivery project where you're equally happy coding and tech-leading the team to implement the solution.

Job responsibilities

·      You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems

·      You will partner with teammates to create complex data processing pipelines in order to solve our clients' most ambitious challenges

·      You will collaborate with Data Scientists in order to design scalable implementations of their models

·      You will pair to write clean and iterative code based on TDD

·      Leverage various continuous delivery practices to deploy, support and operate data pipelines

·      Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available

·      Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions

·      Create data models and speak to the tradeoffs of different modeling approaches

·      On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product

·      Seamlessly incorporate data quality into your day-to-day work as well as into the delivery process

·      Assure effective collaboration between Thoughtworks' and the client's teams, encouraging open communication and advocating for shared outcomes

Job qualifications Technical skills

·      You are equally happy coding and leading a team to implement a solution

·      You have a track record of innovation and expertise in Data Engineering

·      You're passionate about craftsmanship and have applied your expertise across a range of industries and organizations

·      You have a deep understanding of data modelling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop

·      You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting

·      Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions

·      You are comfortable taking data-driven approaches and applying data security strategy to solve business problems

·      You're genuinely excited about data infrastructure and operations with a familiarity working in cloud environments

·      Working with data excites you: you have created Big data architecture, you can build and operate data pipelines, and maintain data storage, all within distributed systems

Professional skills

·      Advocate your data engineering expertise to the broader tech community outside of Thoughtworks, speaking at conferences and acting as a mentor for more junior-level data engineers

·      You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives

·      An interest in coaching others, sharing your experience and knowledge with teammates

·      You enjoy influencing others and always advocate for technical excellence while being open to change when needed

We have immediate requirements for Fresher in BPO Semi Voice Process @ Chennai

Interview Scheduled:

• Walk-in: Monday to Friday (10 AM to 4 PM)

Contact Details:

• Reference Name: PRAVALIKA- HR

Job Description:

• Process : International Semi Voice Process
• Designation: Customer Support Executive
• Qualification : Any graduation (Arts & Science, Engineering) / Diploma / ITI / 12th / Distance Education / Dropout ( 2017- 2021 passed outs only)
• Shift Timings: Night Shift (7.30PM - 5.30AM)
• Salary: 8,500 + Incentives Upto 3000(based on your performance) +Food & Refreshment
• Age limit : 18 - 26 Yrs.
• Work Location: Nungambakkam, Chennai.

About Turing:

Turing enables U.S. companies to hire the world’s best remote software engineers. 100+ companies including those backed by Sequoia, Andreessen, Google Ventures, Benchmark, Founders Fund, Kleiner, Lightspeed, and Bessemer have hired Turing engineers. For more than 180,000 engineers across 140 countries, we are the preferred platform for finding remote U.S. software engineering roles. We offer a wide range of full-time remote opportunities for full-stack, backend, frontend, DevOps, mobile, and AI/ML engineers.

We are growing fast (our revenue 15x’d in the past 12 months and is accelerating), and we have raised $14M in seed funding (https://tcrn.ch/3lNKbM9">one of the largest in Silicon Valley) from:

• Facebook’s 1st CTO and Quora’s Co-Founder (Adam D’Angelo)
• Executives from Google, Facebook, Square, Amazon, and Twitter
• Foundation Capital (investors in Uber, Netflix, Chegg, Lending Club, etc.)
• Cyan Banister
• Founder of Upwork (Beerud Sheth)

We also raised a much larger round of funding in October 2020 that we will be publicly announcing over the coming month. 

Some articles about Turing:

• https://techcrunch.com/2020/08/25/turing-raises-14m-to-help-source-vet-place-and-manage-remote-developers-in-tech-jobs/">TechCrunch: Turing raises $14M seed to help source, vet, place, and manage remote developers
• https://www.theinformation.com/articles/six-startups-prospering-during-coronavirus">The Information: Six Startups Prospering During Coronavirus
• https://medium.com/@cyanbanister/turing-helps-the-world-level-up-ff44b4e6415d">Cyan Banister: Turing Helps the World Level Up
• https://turing.com/boundarylessblog/2019/10/the-future-of-work-is-remote/the-future-of-work/">Jonathan Siddharth (Turing CEO): The Future of Work is Remote.

Turing is led by successful repeat founders Jonathan Siddharth and Vijay Krishnan, whose last A.I. company leveraged elite remote talent and had a successful acquisition. (https://techcrunch.com/2017/02/23/revcontent-acquires-rover/">Techcrunch story). Turing’s leadership team is composed of ex-Engineering and Sales leadership from Facebook, Google, Uber, and Capgemini.

About the role:

Software developers from all over the world have taken 200,000+ tests and interviews on Turing. Turing has also recommended thousands of developers to its customers and got customer feedback in terms of customer interview pass/fail data and data from the success of the collaboration with a U.S customer. This generates a massive proprietary dataset with a rich feature set comprising resume and test/interview features and labels in the form of actual customer feedback. Continuing rapid growth in our business creates an ever-increasing data advantage for us. 

We are looking for a Machine Learning Scientist who can help solve a whole range of exciting and valuable machine learning problems at Turing. Turing collects a lot of valuable heterogeneous signals about software developers including their resume, GitHub profile and associated code and a lot of fine-grained signals from Turing’s own screening tests and interviews (that span various areas including Computer Science fundamentals, project ownership and collaboration, communication skills, proactivity and tech stack skills), their history of successful collaboration with different companies on Turing, etc. 

A machine learning scientist at Turing will help create deep developer profiles that are a good representation of a developer’s strengths and weaknesses as it relates to their probability of getting successfully matched to one of Turing’s partner companies and having a fruitful long-term collaboration. The ML scientist will build models that are able to rank developers for different jobs based on their probability of success at the job. 

     
 You will also help make Turing’s tests more efficient by assessing their ability to predict the probability of a successful match of a developer with at least one company. The prior probability of a registered developer getting matched with a customer is about 1%. We want our tests to adaptively reduce perplexity as steeply as possible and move this probability estimate rapidly toward either 0% or 100%; maximize expected information-gain per unit time in other words. 

As an ML Scientist on the team, you will have a unique opportunity to make an impact by advancing ML models and systems, as well as uncovering new opportunities to apply machine learning concepts to Turing product(s).

This role will directly report to Turing’s founder and CTO, https://www.linkedin.com/in/vijay0/">Vijay Krishnan. This is his https://scholar.google.com/citations?user=uCRc7DgAAAAJ&;hl=en">Google Scholar profile. 

Responsibilities:

• Enhance our existing machine learning systems using your core coding skills and ML knowledge.
• Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems.
• Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics.
• Design features and builds large scale recommendation systems to improve targeting and engagement.
• Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers.

Minimum Requirements:

• BS, MS, or Ph.D. in Computer Science or a relevant technical field (AI/ML preferred).
• Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
• Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance and Data mining, understanding of NLP approaches like W2V or Bert.
• 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing.
• Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them.
• Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
• Good understanding of mathematical foundations of machine learning algorithms.
• Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST).

Other Nice-to-have Requirements:

• First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals. 
• Strong performance in Kaggle competitions.
• 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
• Strong communication skills.
• Experienced in leading large-scale multi-engineering projects.
• Flexible, and a positive team player with outstanding interpersonal skills.