Statusneo

🔹 Role: Erlang Developer – Distributed Systems (Strict OTP Focus)

🔹 What You Will Do

• Design and build fault-tolerant distributed systems using Erlang/OTP
• Develop highly concurrent, real-time backend services
• Architect systems using:
• message passing
• actor model concurrency
• Build and maintain:
• supervision trees
• multi-node clusters
• Ensure:
• high availability (99.99% uptime)
• graceful failure recovery
• Debug:
• production issues in distributed environments
• Work on telecom / messaging / real-time platforms

🔹 Mandatory Skills (NON-NEGOTIABLE)

✅ Core (Must Have)

• Erlang (Recent & Production Experience)
• OTP framework
• GenServer
• Supervisor
• FSM
• Distributed Erlang
• clustering
• node communication

✅ Systems Knowledge

• Distributed systems design
• Actor model / message passing
• Fault tolerance patterns

✅ Erlang Ecosystem (Strong Indicators)

• Mnesia / ETS
• Riak
• Cowboy / Inets
• Rebar3 / Relx

✅ Platform & Infra

• Linux (debugging, system behavior)
• Networking (TCP, SNMP, SIP, HTTP)
• Messaging systems (Kafka / RabbitMQ)
• Databases:
• PostgreSQL / Mnesia

🔹 Experience Requirement

• 4–10 years backend experience
• 3+ years hands-on Erlang (recent)
• Production system ownership

Responsibilities Description:

Responsible for the development and implementation of machine learning algorithms and techniques to solve business problems and optimize member experiences. Primary duties may include are but not limited to: Design machine learning projects to address specific business problems determined by consultation with business partners. Work with data-sets of varying degrees of size and complexity including both structured and unstructured data. Piping and processing massive data-streams in distributed computing environments such as Hadoop to facilitate analysis. Implements batch and real-time model scoring to drive actions. Develops machine learning algorithms to build customized solutions that go beyond standard industry tools and lead to innovative solutions. Develop sophisticated visualization of analysis output for business users.

Experience Requirements:

BS/MA/MS/PhD in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines. 2-4 years of experience in predictive analytics and advanced expertise with software such as Python, or any combination of education and experience which would provide an equivalent background. Experience in the healthcare sector. Experience in Deep Learning strongly preferred.

Required Technical Skill Set:

• Full cycle of building machine learning solutions,

o   Understanding of wide range of algorithms and their corresponding problems to solve

o   Data preparation and analysis

o   Model training and validation

o   Model application to the problem

• Experience using the full open source programming tools and utilities
• Experience in working in end-to-end data science project implementation.
• 2+ years of experience with development and deployment of Machine Learning applications
• 2+ years of experience with NLP approaches in a production setting
• Experience in building models using bagging and boosting algorithms
• Exposure/experience in building Deep Learning models for NLP/Computer Vision use cases preferred
• Ability to write efficient code with good understanding of core Data Structures/algorithms is critical
• Strong python skills following software engineering best practices
• Experience in using code versioning tools like GIT, bit bucket
• Experience in working in Agile projects
• Comfort & familiarity with SQL and Hadoop ecosystem of tools including spark
• Experience managing big data with efficient query program good to have
• Good to have experience in training ML models in tools like Sage Maker, Kubeflow etc.
• Good to have experience in frameworks to depict interpretability of models using libraries like Lime, Shap etc.
• Experience with Health care sector is preferred
• MS/M.Tech or PhD is a plus